Overview

Dataset statistics

Number of variables78
Number of observations422
Missing cells8524
Missing cells (%)25.9%
Total size in memory2.8 MiB
Average record size in memory6.7 KiB

Variable types

Numeric1
Text73
Unsupported1
URL3

Alerts

expected_grade_span_max has constant value ""Constant
last_year_bus has constant value ""Constant
last_year_subway has constant value ""Constant
state_code has constant value ""Constant
eighth_priority08 has constant value ""Constant
ninth_priority09 has constant value ""Constant
tenth_priority10 has constant value ""Constant
context has constant value ""Constant
type has constant value ""Constant
fax_number has 19 (4.5%) missing valuesMissing
expected_grade_span_min has 388 (91.9%) missing valuesMissing
expected_grade_span_max has 386 (91.5%) missing valuesMissing
last_year_bus has 420 (99.5%) missing valuesMissing
last_year_subway has 350 (82.9%) missing valuesMissing
subway has 8 (1.9%) missing valuesMissing
total_student_10_26 has 16 (3.8%) missing valuesMissing
campus_name has 213 (50.5%) missing valuesMissing
second_priority02 has 84 (19.9%) missing valuesMissing
third_priority03 has 193 (45.7%) missing valuesMissing
fourth_priority04 has 257 (60.9%) missing valuesMissing
fifth_priority05 has 382 (90.5%) missing valuesMissing
sixth_priority06 has 404 (95.7%) missing valuesMissing
seventh_priority07 has 417 (98.8%) missing valuesMissing
eighth_priority08 has 421 (99.8%) missing valuesMissing
ninth_priority09 has 421 (99.8%) missing valuesMissing
tenth_priority10 has 421 (99.8%) missing valuesMissing
eleventh_priority11 has 422 (100.0%) missing valuesMissing
email has 62 (14.7%) missing valuesMissing
school_type has 338 (80.1%) missing valuesMissing
language_classes has 30 (7.1%) missing valuesMissing
advanced_placement_courses has 118 (28.0%) missing valuesMissing
psal_sports_boys has 73 (17.3%) missing valuesMissing
psal_sports_girls has 71 (16.8%) missing valuesMissing
psal_sports_co_ed has 290 (68.7%) missing valuesMissing
school_sports has 123 (29.1%) missing valuesMissing
import_info_drop_down has 201 (47.6%) missing valuesMissing
import_info_free_text has 84 (19.9%) missing valuesMissing
online_ap_courses has 376 (89.1%) missing valuesMissing
online_language_courses has 370 (87.7%) missing valuesMissing
header01 has 397 (94.1%) missing valuesMissing
footer01 has 397 (94.1%) missing valuesMissing
school_type2 has 338 (80.1%) missing valuesMissing
0 has unique valuesUnique
dbn has unique valuesUnique
bn has unique valuesUnique
printed_name has unique valuesUnique
alphabetic_name_long has unique valuesUnique
id has unique valuesUnique
eleventh_priority11 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-09 22:20:44.095801
Analysis finished2023-12-09 22:20:48.576602
Duration4.48 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

0
Real number (ℝ)

UNIQUE 

Distinct422
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean211.5
Minimum1
Maximum422
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2023-12-09T22:20:48.980780image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile22.05
Q1106.25
median211.5
Q3316.75
95-th percentile400.95
Maximum422
Range421
Interquartile range (IQR)210.5

Descriptive statistics

Standard deviation121.965159
Coefficient of variation (CV)0.5766674182
Kurtosis-1.2
Mean211.5
Median Absolute Deviation (MAD)105.5
Skewness0
Sum89253
Variance14875.5
MonotonicityStrictly increasing
2023-12-09T22:20:49.150804image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
265 1
 
0.2%
289 1
 
0.2%
288 1
 
0.2%
287 1
 
0.2%
286 1
 
0.2%
285 1
 
0.2%
284 1
 
0.2%
283 1
 
0.2%
282 1
 
0.2%
Other values (412) 412
97.6%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
ValueCountFrequency (%)
422 1
0.2%
421 1
0.2%
420 1
0.2%
419 1
0.2%
418 1
0.2%

dbn
Text

UNIQUE 

Distinct422
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size26.1 KiB
2023-12-09T22:20:50.045637image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters2532
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique422 ?
Unique (%)100.0%

Sample

1st row01M292
2nd row01M448
3rd row01M450
4th row01M509
5th row01M539
ValueCountFrequency (%)
10x433 1
 
0.2%
14k610 1
 
0.2%
27q262 1
 
0.2%
06m423 1
 
0.2%
07x548 1
 
0.2%
18k567 1
 
0.2%
12x278 1
 
0.2%
11x265 1
 
0.2%
21k559 1
 
0.2%
20k490 1
 
0.2%
Other values (412) 412
97.6%
2023-12-09T22:20:50.698525image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 331
13.1%
0 320
12.6%
1 259
10.2%
4 246
9.7%
5 241
9.5%
3 193
7.6%
6 146
 
5.8%
9 135
 
5.3%
8 122
 
4.8%
K 118
 
4.7%
Other values (5) 421
16.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2110
83.3%
Uppercase Letter 422
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 331
15.7%
0 320
15.2%
1 259
12.3%
4 246
11.7%
5 241
11.4%
3 193
9.1%
6 146
6.9%
9 135
6.4%
8 122
 
5.8%
7 117
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
K 118
28.0%
X 116
27.5%
M 102
24.2%
Q 76
18.0%
R 10
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 2110
83.3%
Latin 422
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
2 331
15.7%
0 320
15.2%
1 259
12.3%
4 246
11.7%
5 241
11.4%
3 193
9.1%
6 146
6.9%
9 135
6.4%
8 122
 
5.8%
7 117
 
5.5%
Latin
ValueCountFrequency (%)
K 118
28.0%
X 116
27.5%
M 102
24.2%
Q 76
18.0%
R 10
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2532
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 331
13.1%
0 320
12.6%
1 259
10.2%
4 246
9.7%
5 241
9.5%
3 193
7.6%
6 146
 
5.8%
9 135
 
5.3%
8 122
 
4.8%
K 118
 
4.7%
Other values (5) 421
16.6%

boro
Text

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
2023-12-09T22:20:50.856135image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters422
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowM
2nd rowM
3rd rowM
4th rowM
5th rowM
ValueCountFrequency (%)
k 118
28.0%
x 116
27.5%
m 102
24.2%
q 76
18.0%
r 10
 
2.4%
2023-12-09T22:20:51.109705image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
K 118
28.0%
X 116
27.5%
M 102
24.2%
Q 76
18.0%
R 10
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 422
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 118
28.0%
X 116
27.5%
M 102
24.2%
Q 76
18.0%
R 10
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 422
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 118
28.0%
X 116
27.5%
M 102
24.2%
Q 76
18.0%
R 10
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 422
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K 118
28.0%
X 116
27.5%
M 102
24.2%
Q 76
18.0%
R 10
 
2.4%

bn
Text

UNIQUE 

Distinct422
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size25.3 KiB
2023-12-09T22:20:51.594696image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters1688
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique422 ?
Unique (%)100.0%

Sample

1st rowM292
2nd rowM448
3rd rowM450
4th rowM509
5th rowM539
ValueCountFrequency (%)
m157 1
 
0.2%
q687 1
 
0.2%
k617 1
 
0.2%
m300 1
 
0.2%
k656 1
 
0.2%
q440 1
 
0.2%
q281 1
 
0.2%
x368 1
 
0.2%
k404 1
 
0.2%
x545 1
 
0.2%
Other values (412) 412
97.6%
2023-12-09T22:20:52.225460image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 211
12.5%
4 209
12.4%
2 155
9.2%
3 136
8.1%
6 126
7.5%
0 119
 
7.0%
K 118
 
7.0%
X 116
 
6.9%
M 102
 
6.0%
9 90
 
5.3%
Other values (5) 306
18.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1266
75.0%
Uppercase Letter 422
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 211
16.7%
4 209
16.5%
2 155
12.2%
3 136
10.7%
6 126
10.0%
0 119
9.4%
9 90
7.1%
8 78
 
6.2%
7 72
 
5.7%
1 70
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
K 118
28.0%
X 116
27.5%
M 102
24.2%
Q 76
18.0%
R 10
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 1266
75.0%
Latin 422
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 211
16.7%
4 209
16.5%
2 155
12.2%
3 136
10.7%
6 126
10.0%
0 119
9.4%
9 90
7.1%
8 78
 
6.2%
7 72
 
5.7%
1 70
 
5.5%
Latin
ValueCountFrequency (%)
K 118
28.0%
X 116
27.5%
M 102
24.2%
Q 76
18.0%
R 10
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1688
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 211
12.5%
4 209
12.4%
2 155
9.2%
3 136
8.1%
6 126
7.5%
0 119
 
7.0%
K 118
 
7.0%
X 116
 
6.9%
M 102
 
6.0%
9 90
 
5.3%
Other values (5) 306
18.1%
Distinct253
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size25.3 KiB
2023-12-09T22:20:52.729277image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters1688
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique175 ?
Unique (%)41.5%

Sample

1st rowM056
2nd rowM446
3rd rowM060
4th rowM025
5th rowM022
ValueCountFrequency (%)
x405 6
 
1.4%
x450 6
 
1.4%
x435 6
 
1.4%
x425 6
 
1.4%
k465 5
 
1.2%
m460 5
 
1.2%
m535 5
 
1.2%
k400 5
 
1.2%
x410 5
 
1.2%
m440 5
 
1.2%
Other values (243) 368
87.2%
2023-12-09T22:20:53.382728image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 261
15.5%
0 249
14.8%
5 192
11.4%
K 118
 
7.0%
X 116
 
6.9%
M 102
 
6.0%
6 100
 
5.9%
2 83
 
4.9%
1 82
 
4.9%
7 80
 
4.7%
Other values (5) 305
18.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1266
75.0%
Uppercase Letter 422
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 261
20.6%
0 249
19.7%
5 192
15.2%
6 100
 
7.9%
2 83
 
6.6%
1 82
 
6.5%
7 80
 
6.3%
8 78
 
6.2%
3 76
 
6.0%
9 65
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
K 118
28.0%
X 116
27.5%
M 102
24.2%
Q 76
18.0%
R 10
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 1266
75.0%
Latin 422
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 261
20.6%
0 249
19.7%
5 192
15.2%
6 100
 
7.9%
2 83
 
6.6%
1 82
 
6.5%
7 80
 
6.3%
8 78
 
6.2%
3 76
 
6.0%
9 65
 
5.1%
Latin
ValueCountFrequency (%)
K 118
28.0%
X 116
27.5%
M 102
24.2%
Q 76
18.0%
R 10
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1688
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 261
15.5%
0 249
14.8%
5 192
11.4%
K 118
 
7.0%
X 116
 
6.9%
M 102
 
6.0%
6 100
 
5.9%
2 83
 
4.9%
1 82
 
4.9%
7 80
 
4.7%
Other values (5) 305
18.1%
Distinct416
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
2023-12-09T22:20:53.702178image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters5064
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique413 ?
Unique (%)97.9%

Sample

1st row212-406-9411
2nd row212-962-4341
3rd row212-460-8467
4th row212-473-8152
5th row212-677-5190
ValueCountFrequency (%)
718-381-7100 4
 
0.9%
212-927-1841 3
 
0.7%
718-387-2800 2
 
0.5%
718-387-5641 1
 
0.2%
718-733-5274 1
 
0.2%
718-944-3418 1
 
0.2%
212-246-2183 1
 
0.2%
718-657-3181 1
 
0.2%
718-461-2219 1
 
0.2%
718-797-3702 1
 
0.2%
Other values (406) 406
96.2%
2023-12-09T22:20:54.137978image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 844
16.7%
1 686
13.5%
8 596
11.8%
7 579
11.4%
2 518
10.2%
0 412
8.1%
3 335
 
6.6%
6 292
 
5.8%
4 281
 
5.5%
5 273
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4220
83.3%
Dash Punctuation 844
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 686
16.3%
8 596
14.1%
7 579
13.7%
2 518
12.3%
0 412
9.8%
3 335
7.9%
6 292
6.9%
4 281
6.7%
5 273
 
6.5%
9 248
 
5.9%
Dash Punctuation
ValueCountFrequency (%)
- 844
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5064
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 844
16.7%
1 686
13.5%
8 596
11.8%
7 579
11.4%
2 518
10.2%
0 412
8.1%
3 335
 
6.6%
6 292
 
5.8%
4 281
 
5.5%
5 273
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5064
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 844
16.7%
1 686
13.5%
8 596
11.8%
7 579
11.4%
2 518
10.2%
0 412
8.1%
3 335
 
6.6%
6 292
 
5.8%
4 281
 
5.5%
5 273
 
5.4%

fax_number
Text

MISSING 

Distinct402
Distinct (%)99.8%
Missing19
Missing (%)4.5%
Memory size27.9 KiB
2023-12-09T22:20:54.442105image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters4836
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique401 ?
Unique (%)99.5%

Sample

1st row212-406-9417
2nd row212-267-5611
3rd row212-260-9657
4th row212-475-7588
5th row212-260-8124
ValueCountFrequency (%)
212-674-8021 2
 
0.5%
212-674-1392 1
 
0.2%
212-348-4293 1
 
0.2%
718-922-0953 1
 
0.2%
718-525-6482 1
 
0.2%
212-255-4756 1
 
0.2%
212-253-8095 1
 
0.2%
212-246-2654 1
 
0.2%
212-580-0156 1
 
0.2%
212-576-0562 1
 
0.2%
Other values (392) 392
97.3%
2023-12-09T22:20:55.077114image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 806
16.7%
1 649
13.4%
7 597
12.3%
8 583
12.1%
2 533
11.0%
3 311
 
6.4%
6 306
 
6.3%
5 292
 
6.0%
9 289
 
6.0%
4 268
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4030
83.3%
Dash Punctuation 806
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 649
16.1%
7 597
14.8%
8 583
14.5%
2 533
13.2%
3 311
7.7%
6 306
7.6%
5 292
7.2%
9 289
7.2%
4 268
6.7%
0 202
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 806
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4836
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 806
16.7%
1 649
13.4%
7 597
12.3%
8 583
12.1%
2 533
11.0%
3 311
 
6.4%
6 306
 
6.3%
5 292
 
6.0%
9 289
 
6.0%
4 268
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4836
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 806
16.7%
1 649
13.4%
7 597
12.3%
8 583
12.1%
2 533
11.0%
3 311
 
6.4%
6 306
 
6.3%
5 292
 
6.0%
9 289
 
6.0%
4 268
 
5.5%

printed_name
Text

UNIQUE 

Distinct422
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size38.8 KiB
2023-12-09T22:20:55.446223image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length79
Median length57
Mean length36.74407583
Min length11

Characters and Unicode

Total characters15506
Distinct characters67
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique422 ?
Unique (%)100.0%

Sample

1st rowHenry Street School for International Studies
2nd rowUniversity Neighborhood High School
3rd rowEast Side Community School
4th rowMarta Valle High School
5th rowNew Explorations into Science, Technology and Math High School
ValueCountFrequency (%)
school 327
 
14.3%
high 222
 
9.7%
for 131
 
5.7%
academy 100
 
4.4%
and 95
 
4.1%
the 61
 
2.7%
of 54
 
2.4%
bronx 37
 
1.6%
arts 37
 
1.6%
college 34
 
1.5%
Other values (490) 1196
52.1%
2023-12-09T22:20:55.993150image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1874
 
12.1%
o 1466
 
9.5%
e 1099
 
7.1%
a 911
 
5.9%
n 823
 
5.3%
r 816
 
5.3%
i 809
 
5.2%
h 794
 
5.1%
l 785
 
5.1%
c 740
 
4.8%
Other values (57) 5389
34.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11485
74.1%
Uppercase Letter 2028
 
13.1%
Space Separator 1874
 
12.1%
Other Punctuation 92
 
0.6%
Decimal Number 8
 
0.1%
Open Punctuation 7
 
< 0.1%
Close Punctuation 7
 
< 0.1%
Dash Punctuation 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1466
12.8%
e 1099
9.6%
a 911
 
7.9%
n 823
 
7.2%
r 816
 
7.1%
i 809
 
7.0%
h 794
 
6.9%
l 785
 
6.8%
c 740
 
6.4%
t 545
 
4.7%
Other values (16) 2697
23.5%
Uppercase Letter
ValueCountFrequency (%)
S 451
22.2%
H 285
14.1%
A 212
10.5%
C 161
 
7.9%
T 111
 
5.5%
B 108
 
5.3%
E 86
 
4.2%
M 86
 
4.2%
L 80
 
3.9%
P 77
 
3.8%
Other values (14) 371
18.3%
Other Punctuation
ValueCountFrequency (%)
. 27
29.3%
, 24
26.1%
: 16
17.4%
& 13
14.1%
' 6
 
6.5%
/ 4
 
4.3%
" 2
 
2.2%
Decimal Number
ValueCountFrequency (%)
1 2
25.0%
4 2
25.0%
7 1
12.5%
3 1
12.5%
6 1
12.5%
8 1
12.5%
Space Separator
ValueCountFrequency (%)
1874
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13513
87.1%
Common 1993
 
12.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1466
 
10.8%
e 1099
 
8.1%
a 911
 
6.7%
n 823
 
6.1%
r 816
 
6.0%
i 809
 
6.0%
h 794
 
5.9%
l 785
 
5.8%
c 740
 
5.5%
t 545
 
4.0%
Other values (40) 4725
35.0%
Common
ValueCountFrequency (%)
1874
94.0%
. 27
 
1.4%
, 24
 
1.2%
: 16
 
0.8%
& 13
 
0.7%
( 7
 
0.4%
) 7
 
0.4%
' 6
 
0.3%
- 5
 
0.3%
/ 4
 
0.2%
Other values (7) 10
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15506
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1874
 
12.1%
o 1466
 
9.5%
e 1099
 
7.1%
a 911
 
5.9%
n 823
 
5.3%
r 816
 
5.3%
i 809
 
5.2%
h 794
 
5.1%
l 785
 
5.1%
c 740
 
4.8%
Other values (57) 5389
34.8%
Distinct422
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size38.8 KiB
2023-12-09T22:20:56.372627image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length79
Median length57
Mean length36.83175355
Min length11

Characters and Unicode

Total characters15543
Distinct characters67
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique422 ?
Unique (%)100.0%

Sample

1st rowHenry Street School for International Studies
2nd rowUniversity Neighborhood High School
3rd rowEast Side Community School
4th rowMarta Valle High School
5th rowNew Explorations into Science, Technology and Math High School
ValueCountFrequency (%)
school 327
 
14.3%
high 222
 
9.7%
for 131
 
5.7%
academy 100
 
4.4%
and 95
 
4.1%
the 61
 
2.7%
of 54
 
2.4%
bronx 37
 
1.6%
arts 37
 
1.6%
college 34
 
1.5%
Other values (490) 1196
52.1%
2023-12-09T22:20:56.938234image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1874
 
12.1%
o 1466
 
9.4%
e 1099
 
7.1%
a 911
 
5.9%
n 823
 
5.3%
r 816
 
5.2%
i 809
 
5.2%
h 794
 
5.1%
l 785
 
5.1%
c 740
 
4.8%
Other values (57) 5426
34.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11485
73.9%
Uppercase Letter 2028
 
13.0%
Space Separator 1874
 
12.1%
Other Punctuation 129
 
0.8%
Decimal Number 8
 
0.1%
Open Punctuation 7
 
< 0.1%
Close Punctuation 7
 
< 0.1%
Dash Punctuation 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1466
12.8%
e 1099
9.6%
a 911
 
7.9%
n 823
 
7.2%
r 816
 
7.1%
i 809
 
7.0%
h 794
 
6.9%
l 785
 
6.8%
c 740
 
6.4%
t 545
 
4.7%
Other values (16) 2697
23.5%
Uppercase Letter
ValueCountFrequency (%)
S 451
22.2%
H 285
14.1%
A 212
10.5%
C 161
 
7.9%
T 111
 
5.5%
B 108
 
5.3%
E 86
 
4.2%
M 86
 
4.2%
L 80
 
3.9%
P 77
 
3.8%
Other values (14) 371
18.3%
Other Punctuation
ValueCountFrequency (%)
, 61
47.3%
. 27
20.9%
: 16
 
12.4%
& 13
 
10.1%
' 6
 
4.7%
/ 4
 
3.1%
" 2
 
1.6%
Decimal Number
ValueCountFrequency (%)
1 2
25.0%
4 2
25.0%
7 1
12.5%
3 1
12.5%
6 1
12.5%
8 1
12.5%
Space Separator
ValueCountFrequency (%)
1874
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13513
86.9%
Common 2030
 
13.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1466
 
10.8%
e 1099
 
8.1%
a 911
 
6.7%
n 823
 
6.1%
r 816
 
6.0%
i 809
 
6.0%
h 794
 
5.9%
l 785
 
5.8%
c 740
 
5.5%
t 545
 
4.0%
Other values (40) 4725
35.0%
Common
ValueCountFrequency (%)
1874
92.3%
, 61
 
3.0%
. 27
 
1.3%
: 16
 
0.8%
& 13
 
0.6%
( 7
 
0.3%
) 7
 
0.3%
' 6
 
0.3%
- 5
 
0.2%
/ 4
 
0.2%
Other values (7) 10
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15543
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1874
 
12.1%
o 1466
 
9.4%
e 1099
 
7.1%
a 911
 
5.9%
n 823
 
5.3%
r 816
 
5.2%
i 809
 
5.2%
h 794
 
5.1%
l 785
 
5.1%
c 740
 
4.8%
Other values (57) 5426
34.9%
Distinct4
Distinct (%)1.0%
Missing4
Missing (%)0.9%
Memory size23.9 KiB
2023-12-09T22:20:57.065744image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters418
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row6
2nd row9
3rd row6
4th row9
5th row9
ValueCountFrequency (%)
9 340
81.3%
6 75
 
17.9%
7 2
 
0.5%
8 1
 
0.2%
2023-12-09T22:20:57.289768image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 340
81.3%
6 75
 
17.9%
7 2
 
0.5%
8 1
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 418
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 340
81.3%
6 75
 
17.9%
7 2
 
0.5%
8 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 418
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 340
81.3%
6 75
 
17.9%
7 2
 
0.5%
8 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 418
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 340
81.3%
6 75
 
17.9%
7 2
 
0.5%
8 1
 
0.2%
Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size24.4 KiB
2023-12-09T22:20:57.410485image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters844
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row12
2nd row12
3rd row12
4th row12
5th row12
ValueCountFrequency (%)
12 389
92.2%
10 19
 
4.5%
11 14
 
3.3%
2023-12-09T22:20:57.642499image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 436
51.7%
2 389
46.1%
0 19
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 844
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 436
51.7%
2 389
46.1%
0 19
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 844
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 436
51.7%
2 389
46.1%
0 19
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 844
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 436
51.7%
2 389
46.1%
0 19
 
2.3%
Distinct2
Distinct (%)5.9%
Missing388
Missing (%)91.9%
Memory size14.2 KiB
2023-12-09T22:20:57.752652image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters34
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6
2nd row9
3rd row9
4th row9
5th row6
ValueCountFrequency (%)
9 27
79.4%
6 7
 
20.6%
2023-12-09T22:20:57.981617image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 27
79.4%
6 7
 
20.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 27
79.4%
6 7
 
20.6%

Most occurring scripts

ValueCountFrequency (%)
Common 34
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 27
79.4%
6 7
 
20.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 27
79.4%
6 7
 
20.6%

expected_grade_span_max
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)2.8%
Missing386
Missing (%)91.5%
Memory size14.3 KiB
2023-12-09T22:20:58.089784image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters72
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row12
2nd row12
3rd row12
4th row12
5th row12
ValueCountFrequency (%)
12 36
100.0%
2023-12-09T22:20:58.322513image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 36
50.0%
2 36
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 36
50.0%
2 36
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 72
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 36
50.0%
2 36
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 72
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 36
50.0%
2 36
50.0%

last_year_bus
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing420
Missing (%)99.5%
Memory size13.4 KiB
2023-12-09T22:20:58.433078image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
ValueCountFrequency (%)
1 2
100.0%
2023-12-09T22:20:58.650938image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
100.0%

bus
Text

Distinct232
Distinct (%)55.1%
Missing1
Missing (%)0.2%
Memory size38.0 KiB
2023-12-09T22:20:59.159260image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length140
Median length59
Mean length35.0807601
Min length3

Characters and Unicode

Total characters14769
Distinct characters21
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique146 ?
Unique (%)34.7%

Sample

1st rowM14AD, M15, M21, M22, M9
2nd rowM14AD, M15, M21, M22, M9
3rd rowM1, M101, M103, M14AD, M15, M15-SBS, M23, M3, M8, M9
4th rowM103, M14AD, M15, M15-SBS, M21, M22, M8, M9
5th rowM14AD, M21, M22, M8, M9
ValueCountFrequency (%)
m5 54
 
1.8%
bx15 49
 
1.6%
bx41 45
 
1.5%
bx17 45
 
1.5%
m15 44
 
1.5%
m101 44
 
1.5%
bx1 43
 
1.4%
bx19 41
 
1.4%
m7 40
 
1.3%
bx21 38
 
1.3%
Other values (223) 2528
85.1%
2023-12-09T22:20:59.874792image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2550
17.3%
, 2545
17.2%
B 1602
10.8%
1 1215
8.2%
X 815
 
5.5%
M 795
 
5.4%
2 704
 
4.8%
4 645
 
4.4%
5 602
 
4.1%
3 584
 
4.0%
Other values (11) 2712
18.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5529
37.4%
Uppercase Letter 4073
27.6%
Space Separator 2550
17.3%
Other Punctuation 2545
17.2%
Dash Punctuation 63
 
0.4%
Lowercase Letter 9
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1215
22.0%
2 704
12.7%
4 645
11.7%
5 602
10.9%
3 584
10.6%
6 511
9.2%
0 442
 
8.0%
7 348
 
6.3%
8 248
 
4.5%
9 230
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
B 1602
39.3%
X 815
20.0%
M 795
19.5%
Q 572
 
14.0%
S 187
 
4.6%
A 71
 
1.7%
D 31
 
0.8%
Space Separator
ValueCountFrequency (%)
2550
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2545
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 63
100.0%
Lowercase Letter
ValueCountFrequency (%)
x 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10687
72.4%
Latin 4082
 
27.6%

Most frequent character per script

Common
ValueCountFrequency (%)
2550
23.9%
, 2545
23.8%
1 1215
11.4%
2 704
 
6.6%
4 645
 
6.0%
5 602
 
5.6%
3 584
 
5.5%
6 511
 
4.8%
0 442
 
4.1%
7 348
 
3.3%
Other values (3) 541
 
5.1%
Latin
ValueCountFrequency (%)
B 1602
39.2%
X 815
20.0%
M 795
19.5%
Q 572
 
14.0%
S 187
 
4.6%
A 71
 
1.7%
D 31
 
0.8%
x 9
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14769
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2550
17.3%
, 2545
17.2%
B 1602
10.8%
1 1215
8.2%
X 815
 
5.5%
M 795
 
5.4%
2 704
 
4.8%
4 645
 
4.4%
5 602
 
4.1%
3 584
 
4.0%
Other values (11) 2712
18.4%

last_year_subway
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)1.4%
Missing350
Missing (%)82.9%
Memory size15.1 KiB
2023-12-09T22:20:59.995611image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters72
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 72
100.0%
2023-12-09T22:21:00.228177image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 72
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 72
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 72
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 72
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 72
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 72
100.0%

subway
Text

MISSING 

Distinct237
Distinct (%)57.2%
Missing8
Missing (%)1.9%
Memory size43.4 KiB
2023-12-09T22:21:00.534711image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length205
Median length119.5
Mean length49.41062802
Min length7

Characters and Unicode

Total characters20456
Distinct characters71
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique159 ?
Unique (%)38.4%

Sample

1st rowJ, M, Z to Delancey St-Essex St; F to East Broadway; B, D to Grand St
2nd rowJ, M, Z to Delancey St-Essex St; F to East Broadway
3rd rowL to 1st Av; 6 to Astor Place
4th rowF, J, M, Z to Delancey St-Essex St; B, D to Grand St
5th rowF, J, M, Z to Delancey St-Essex St
ValueCountFrequency (%)
to 853
 
17.5%
st 372
 
7.6%
av 210
 
4.3%
169
 
3.5%
2 142
 
2.9%
5 130
 
2.7%
b 119
 
2.4%
d 105
 
2.2%
4 95
 
2.0%
f 94
 
1.9%
Other values (334) 2581
53.0%
2023-12-09T22:21:01.034697image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4829
23.6%
t 2064
 
10.1%
o 1333
 
6.5%
, 866
 
4.2%
e 757
 
3.7%
r 697
 
3.4%
a 668
 
3.3%
S 625
 
3.1%
n 560
 
2.7%
h 470
 
2.3%
Other values (61) 7587
37.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9392
45.9%
Space Separator 4829
23.6%
Uppercase Letter 3043
 
14.9%
Decimal Number 1552
 
7.6%
Other Punctuation 1336
 
6.5%
Dash Punctuation 294
 
1.4%
Open Punctuation 5
 
< 0.1%
Close Punctuation 5
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 625
20.5%
A 376
12.4%
B 250
 
8.2%
C 221
 
7.3%
F 148
 
4.9%
M 141
 
4.6%
D 135
 
4.4%
R 129
 
4.2%
P 117
 
3.8%
G 110
 
3.6%
Other values (16) 791
26.0%
Lowercase Letter
ValueCountFrequency (%)
t 2064
22.0%
o 1333
14.2%
e 757
 
8.1%
r 697
 
7.4%
a 668
 
7.1%
n 560
 
6.0%
h 470
 
5.0%
l 366
 
3.9%
s 329
 
3.5%
v 303
 
3.2%
Other values (15) 1845
19.6%
Decimal Number
ValueCountFrequency (%)
1 293
18.9%
2 222
14.3%
5 205
13.2%
4 195
12.6%
3 179
11.5%
6 165
10.6%
7 116
 
7.5%
9 75
 
4.8%
8 53
 
3.4%
0 49
 
3.2%
Other Punctuation
ValueCountFrequency (%)
, 866
64.8%
; 446
33.4%
/ 20
 
1.5%
' 2
 
0.1%
. 1
 
0.1%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
4829
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 294
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12435
60.8%
Common 8021
39.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 2064
16.6%
o 1333
 
10.7%
e 757
 
6.1%
r 697
 
5.6%
a 668
 
5.4%
S 625
 
5.0%
n 560
 
4.5%
h 470
 
3.8%
A 376
 
3.0%
l 366
 
2.9%
Other values (41) 4519
36.3%
Common
ValueCountFrequency (%)
4829
60.2%
, 866
 
10.8%
; 446
 
5.6%
- 294
 
3.7%
1 293
 
3.7%
2 222
 
2.8%
5 205
 
2.6%
4 195
 
2.4%
3 179
 
2.2%
6 165
 
2.1%
Other values (10) 327
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20456
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4829
23.6%
t 2064
 
10.1%
o 1333
 
6.5%
, 866
 
4.2%
e 757
 
3.7%
r 697
 
3.4%
a 668
 
3.3%
S 625
 
3.1%
n 560
 
2.7%
h 470
 
2.3%
Other values (61) 7587
37.1%
Distinct258
Distinct (%)61.1%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
2023-12-09T22:21:01.395200image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length33
Median length28
Mean length18.91469194
Min length11

Characters and Unicode

Total characters7982
Distinct characters61
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique182 ?
Unique (%)43.1%

Sample

1st row220 Henry Street
2nd row200 Monroe Street
3rd row420 East 12 Street
4th row145 Stanton Street
5th row111 Columbia Street
ValueCountFrequency (%)
avenue 181
 
12.8%
street 157
 
11.1%
east 54
 
3.8%
west 47
 
3.3%
road 27
 
1.9%
boulevard 13
 
0.9%
place 10
 
0.7%
irving 9
 
0.6%
350 9
 
0.6%
grand 9
 
0.6%
Other values (447) 901
63.6%
2023-12-09T22:21:02.155259image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1002
 
12.6%
e 941
 
11.8%
t 564
 
7.1%
n 393
 
4.9%
0 340
 
4.3%
r 340
 
4.3%
1 319
 
4.0%
a 316
 
4.0%
u 244
 
3.1%
o 236
 
3.0%
Other values (51) 3287
41.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4267
53.5%
Decimal Number 1730
21.7%
Space Separator 1002
 
12.6%
Uppercase Letter 892
 
11.2%
Dash Punctuation 79
 
1.0%
Other Punctuation 12
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 941
22.1%
t 564
13.2%
n 393
9.2%
r 340
 
8.0%
a 316
 
7.4%
u 244
 
5.7%
o 236
 
5.5%
v 230
 
5.4%
s 217
 
5.1%
l 129
 
3.0%
Other values (13) 657
15.4%
Uppercase Letter
ValueCountFrequency (%)
A 212
23.8%
S 187
21.0%
B 64
 
7.2%
E 62
 
7.0%
W 54
 
6.1%
R 41
 
4.6%
T 40
 
4.5%
P 34
 
3.8%
G 28
 
3.1%
F 25
 
2.8%
Other values (13) 145
16.3%
Decimal Number
ValueCountFrequency (%)
0 340
19.7%
1 319
18.4%
2 198
11.4%
5 194
11.2%
3 159
9.2%
4 143
8.3%
9 97
 
5.6%
6 97
 
5.6%
7 94
 
5.4%
8 89
 
5.1%
Other Punctuation
ValueCountFrequency (%)
. 10
83.3%
, 1
 
8.3%
' 1
 
8.3%
Space Separator
ValueCountFrequency (%)
1002
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 79
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5159
64.6%
Common 2823
35.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 941
18.2%
t 564
 
10.9%
n 393
 
7.6%
r 340
 
6.6%
a 316
 
6.1%
u 244
 
4.7%
o 236
 
4.6%
v 230
 
4.5%
s 217
 
4.2%
A 212
 
4.1%
Other values (36) 1466
28.4%
Common
ValueCountFrequency (%)
1002
35.5%
0 340
 
12.0%
1 319
 
11.3%
2 198
 
7.0%
5 194
 
6.9%
3 159
 
5.6%
4 143
 
5.1%
9 97
 
3.4%
6 97
 
3.4%
7 94
 
3.3%
Other values (5) 180
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7982
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1002
 
12.6%
e 941
 
11.8%
t 564
 
7.1%
n 393
 
4.9%
0 340
 
4.3%
r 340
 
4.3%
1 319
 
4.0%
a 316
 
4.0%
u 244
 
3.1%
o 236
 
3.0%
Other values (51) 3287
41.2%

city
Text

Distinct26
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size26.9 KiB
2023-12-09T22:21:02.393294image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length19
Median length8
Mean length7.86492891
Min length5

Characters and Unicode

Total characters3319
Distinct characters43
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)2.4%

Sample

1st rowNew York
2nd rowNew York
3rd rowNew York
4th rowNew York
5th rowNew York
ValueCountFrequency (%)
brooklyn 118
20.1%
bronx 116
19.7%
new 102
17.3%
york 102
17.3%
island 23
 
3.9%
jamaica 13
 
2.2%
long 13
 
2.2%
city 13
 
2.2%
staten 10
 
1.7%
flushing 8
 
1.4%
Other values (27) 70
11.9%
2023-12-09T22:21:02.758886image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 496
14.9%
r 376
11.3%
n 306
 
9.2%
B 236
 
7.1%
k 235
 
7.1%
l 174
 
5.2%
166
 
5.0%
e 144
 
4.3%
y 139
 
4.2%
a 122
 
3.7%
Other values (33) 925
27.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2565
77.3%
Uppercase Letter 588
 
17.7%
Space Separator 166
 
5.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 496
19.3%
r 376
14.7%
n 306
11.9%
k 235
9.2%
l 174
 
6.8%
e 144
 
5.6%
y 139
 
5.4%
a 122
 
4.8%
x 116
 
4.5%
w 113
 
4.4%
Other values (13) 344
13.4%
Uppercase Letter
ValueCountFrequency (%)
B 236
40.1%
N 102
17.3%
Y 102
17.3%
I 23
 
3.9%
F 17
 
2.9%
C 17
 
2.9%
S 16
 
2.7%
J 13
 
2.2%
L 13
 
2.2%
R 9
 
1.5%
Other values (9) 40
 
6.8%
Space Separator
ValueCountFrequency (%)
166
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3153
95.0%
Common 166
 
5.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 496
15.7%
r 376
11.9%
n 306
 
9.7%
B 236
 
7.5%
k 235
 
7.5%
l 174
 
5.5%
e 144
 
4.6%
y 139
 
4.4%
a 122
 
3.9%
x 116
 
3.7%
Other values (32) 809
25.7%
Common
ValueCountFrequency (%)
166
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3319
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 496
14.9%
r 376
11.3%
n 306
 
9.2%
B 236
 
7.1%
k 235
 
7.1%
l 174
 
5.2%
166
 
5.0%
e 144
 
4.3%
y 139
 
4.2%
a 122
 
3.7%
Other values (33) 925
27.9%

state_code
Text

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size24.4 KiB
2023-12-09T22:21:02.873598image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters844
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNY
2nd rowNY
3rd rowNY
4th rowNY
5th rowNY
ValueCountFrequency (%)
ny 422
100.0%
2023-12-09T22:21:03.086171image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 422
50.0%
Y 422
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 844
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 422
50.0%
Y 422
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 844
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 422
50.0%
Y 422
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 844
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 422
50.0%
Y 422
50.0%

zip
Text

Distinct117
Distinct (%)27.7%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
2023-12-09T22:21:03.468243image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters2110
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)9.0%

Sample

1st row10002
2nd row10002
3rd row10009
4th row10002
5th row10002
ValueCountFrequency (%)
10457 12
 
2.8%
11101 12
 
2.8%
10002 11
 
2.6%
11201 11
 
2.6%
10456 11
 
2.6%
10468 10
 
2.4%
10019 10
 
2.4%
10451 9
 
2.1%
10473 9
 
2.1%
10011 9
 
2.1%
Other values (107) 318
75.4%
2023-12-09T22:21:03.973297image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 782
37.1%
0 441
20.9%
2 207
 
9.8%
4 184
 
8.7%
3 147
 
7.0%
6 115
 
5.5%
5 98
 
4.6%
7 63
 
3.0%
9 37
 
1.8%
8 36
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2110
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 782
37.1%
0 441
20.9%
2 207
 
9.8%
4 184
 
8.7%
3 147
 
7.0%
6 115
 
5.5%
5 98
 
4.6%
7 63
 
3.0%
9 37
 
1.8%
8 36
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
Common 2110
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 782
37.1%
0 441
20.9%
2 207
 
9.8%
4 184
 
8.7%
3 147
 
7.0%
6 115
 
5.5%
5 98
 
4.6%
7 63
 
3.0%
9 37
 
1.8%
8 36
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2110
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 782
37.1%
0 441
20.9%
2 207
 
9.8%
4 184
 
8.7%
3 147
 
7.0%
6 115
 
5.5%
5 98
 
4.6%
7 63
 
3.0%
9 37
 
1.8%
8 36
 
1.7%

total_student_10_26
Text

MISSING 

Distinct316
Distinct (%)77.8%
Missing16
Missing (%)3.8%
Memory size24.5 KiB
2023-12-09T22:21:04.504557image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.145320197
Min length2

Characters and Unicode

Total characters1277
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique246 ?
Unique (%)60.6%

Sample

1st row388
2nd row331
3rd row636
4th row367
5th row1672
ValueCountFrequency (%)
388 5
 
1.2%
437 4
 
1.0%
416 3
 
0.7%
475 3
 
0.7%
447 3
 
0.7%
476 3
 
0.7%
434 3
 
0.7%
636 3
 
0.7%
398 3
 
0.7%
429 3
 
0.7%
Other values (306) 373
91.9%
2023-12-09T22:21:05.181835image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 192
15.0%
3 179
14.0%
2 152
11.9%
1 136
10.6%
5 123
9.6%
6 112
8.8%
7 109
8.5%
9 101
7.9%
8 93
7.3%
0 80
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1277
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 192
15.0%
3 179
14.0%
2 152
11.9%
1 136
10.6%
5 123
9.6%
6 112
8.8%
7 109
8.5%
9 101
7.9%
8 93
7.3%
0 80
6.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1277
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 192
15.0%
3 179
14.0%
2 152
11.9%
1 136
10.6%
5 123
9.6%
6 112
8.8%
7 109
8.5%
9 101
7.9%
8 93
7.3%
0 80
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1277
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 192
15.0%
3 179
14.0%
2 152
11.9%
1 136
10.6%
5 123
9.6%
6 112
8.8%
7 109
8.5%
9 101
7.9%
8 93
7.3%
0 80
6.3%

campus_name
Text

MISSING 

Distinct65
Distinct (%)31.1%
Missing213
Missing (%)50.5%
Memory size25.0 KiB
2023-12-09T22:21:05.558944image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length37
Mean length32.20095694
Min length19

Characters and Unicode

Total characters6730
Distinct characters48
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)3.8%

Sample

1st rowPark West Educational Campus
2nd rowSeward Park Educational Campus
3rd rowPark West Educational Campus
4th rowPark West Educational Campus
5th rowPark West Educational Campus
ValueCountFrequency (%)
campus 209
24.7%
educational 204
24.1%
park 10
 
1.2%
george 10
 
1.2%
washington 9
 
1.1%
john 8
 
0.9%
e 8
 
0.9%
thomas 7
 
0.8%
theodore 6
 
0.7%
stevenson 6
 
0.7%
Other values (115) 368
43.6%
2023-12-09T22:21:06.076554image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 844
 
12.5%
640
 
9.5%
u 477
 
7.1%
n 391
 
5.8%
o 365
 
5.4%
t 347
 
5.2%
i 341
 
5.1%
s 335
 
5.0%
l 298
 
4.4%
d 289
 
4.3%
Other values (38) 2403
35.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5197
77.2%
Uppercase Letter 850
 
12.6%
Space Separator 640
 
9.5%
Other Punctuation 43
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 844
16.2%
u 477
 
9.2%
n 391
 
7.5%
o 365
 
7.0%
t 347
 
6.7%
i 341
 
6.6%
s 335
 
6.4%
l 298
 
5.7%
d 289
 
5.6%
m 272
 
5.2%
Other values (13) 1238
23.8%
Uppercase Letter
ValueCountFrequency (%)
C 239
28.1%
E 230
27.1%
J 40
 
4.7%
S 40
 
4.7%
H 38
 
4.5%
W 36
 
4.2%
M 28
 
3.3%
T 24
 
2.8%
L 24
 
2.8%
B 22
 
2.6%
Other values (11) 129
15.2%
Other Punctuation
ValueCountFrequency (%)
. 34
79.1%
, 6
 
14.0%
' 3
 
7.0%
Space Separator
ValueCountFrequency (%)
640
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6047
89.9%
Common 683
 
10.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 844
14.0%
u 477
 
7.9%
n 391
 
6.5%
o 365
 
6.0%
t 347
 
5.7%
i 341
 
5.6%
s 335
 
5.5%
l 298
 
4.9%
d 289
 
4.8%
m 272
 
4.5%
Other values (34) 2088
34.5%
Common
ValueCountFrequency (%)
640
93.7%
. 34
 
5.0%
, 6
 
0.9%
' 3
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6730
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 844
 
12.5%
640
 
9.5%
u 477
 
7.1%
n 391
 
5.8%
o 365
 
5.4%
t 347
 
5.2%
i 341
 
5.1%
s 335
 
5.0%
l 298
 
4.4%
d 289
 
4.3%
Other values (38) 2403
35.7%
Distinct11
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
2023-12-09T22:21:06.258779image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length108
Median length3
Mean length8.291469194
Min length3

Characters and Unicode

Total characters3499
Distinct characters35
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)1.2%

Sample

1st rowESL
2nd rowESL; Transitional Bilingual Program: Chinese (Mandarin)
3rd rowESL
4th rowESL
5th rowESL
ValueCountFrequency (%)
esl 422
65.3%
program 49
 
7.6%
transitional 44
 
6.8%
bilingual 44
 
6.8%
spanish 39
 
6.0%
chinese 13
 
2.0%
mandarin 13
 
2.0%
dual 5
 
0.8%
language 5
 
0.8%
haitian 4
 
0.6%
Other values (4) 8
 
1.2%
2023-12-09T22:21:06.564815image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 461
13.2%
L 427
12.2%
E 422
12.1%
a 273
 
7.8%
i 253
 
7.2%
224
 
6.4%
n 222
 
6.3%
r 160
 
4.6%
l 142
 
4.1%
g 104
 
3.0%
Other values (25) 811
23.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1650
47.2%
Uppercase Letter 1490
42.6%
Space Separator 224
 
6.4%
Other Punctuation 109
 
3.1%
Close Punctuation 13
 
0.4%
Open Punctuation 13
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 273
16.5%
i 253
15.3%
n 222
13.5%
r 160
9.7%
l 142
8.6%
g 104
 
6.3%
s 100
 
6.1%
o 97
 
5.9%
u 56
 
3.4%
h 52
 
3.2%
Other values (7) 191
11.6%
Uppercase Letter
ValueCountFrequency (%)
S 461
30.9%
L 427
28.7%
E 422
28.3%
P 49
 
3.3%
B 45
 
3.0%
T 44
 
3.0%
C 17
 
1.1%
M 13
 
0.9%
D 5
 
0.3%
H 4
 
0.3%
Other values (2) 3
 
0.2%
Other Punctuation
ValueCountFrequency (%)
: 49
45.0%
; 49
45.0%
, 11
 
10.1%
Space Separator
ValueCountFrequency (%)
224
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3140
89.7%
Common 359
 
10.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 461
14.7%
L 427
13.6%
E 422
13.4%
a 273
8.7%
i 253
8.1%
n 222
 
7.1%
r 160
 
5.1%
l 142
 
4.5%
g 104
 
3.3%
s 100
 
3.2%
Other values (19) 576
18.3%
Common
ValueCountFrequency (%)
224
62.4%
: 49
 
13.6%
; 49
 
13.6%
) 13
 
3.6%
( 13
 
3.6%
, 11
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3499
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 461
13.2%
L 427
12.2%
E 422
12.1%
a 273
 
7.8%
i 253
 
7.2%
224
 
6.4%
n 222
 
6.3%
r 160
 
4.6%
l 142
 
4.1%
g 104
 
3.0%
Other values (25) 811
23.2%
Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size31.5 KiB
2023-12-09T22:21:06.737454image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length20
Mean length19.07582938
Min length14

Characters and Unicode

Total characters8050
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot Accessible
2nd rowNot Accessible
3rd rowNot Accessible
4th rowFunctionally Accessible
5th rowNot Accessible
ValueCountFrequency (%)
accessible 422
50.0%
functionally 210
24.9%
not 170
20.1%
partially 42
 
5.0%
2023-12-09T22:21:07.020156image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
c 1054
13.1%
l 926
11.5%
s 844
10.5%
e 844
10.5%
i 674
8.4%
t 422
 
5.2%
b 422
 
5.2%
422
 
5.2%
A 422
 
5.2%
n 420
 
5.2%
Other values (8) 1600
19.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6784
84.3%
Uppercase Letter 844
 
10.5%
Space Separator 422
 
5.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 1054
15.5%
l 926
13.6%
s 844
12.4%
e 844
12.4%
i 674
9.9%
t 422
6.2%
b 422
6.2%
n 420
 
6.2%
o 380
 
5.6%
a 294
 
4.3%
Other values (3) 504
7.4%
Uppercase Letter
ValueCountFrequency (%)
A 422
50.0%
F 210
24.9%
N 170
20.1%
P 42
 
5.0%
Space Separator
ValueCountFrequency (%)
422
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7628
94.8%
Common 422
 
5.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 1054
13.8%
l 926
12.1%
s 844
11.1%
e 844
11.1%
i 674
8.8%
t 422
 
5.5%
b 422
 
5.5%
A 422
 
5.5%
n 420
 
5.5%
o 380
 
5.0%
Other values (7) 1220
16.0%
Common
ValueCountFrequency (%)
422
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8050
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
c 1054
13.1%
l 926
11.5%
s 844
10.5%
e 844
10.5%
i 674
8.4%
t 422
 
5.2%
b 422
 
5.2%
422
 
5.2%
A 422
 
5.2%
n 420
 
5.2%
Other values (8) 1600
19.9%
Distinct71
Distinct (%)16.9%
Missing1
Missing (%)0.2%
Memory size50.0 KiB
2023-12-09T22:21:07.356220image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length298
Median length245
Mean length64.11401425
Min length17

Characters and Unicode

Total characters26992
Distinct characters68
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)10.9%

Sample

1st rowPriority to continuing 8th graders
2nd rowOpen to New York City residents
3rd rowPriority to continuing 8th graders
4th rowPriority to District 1 students or residents
5th rowPriority to continuing 8th graders
ValueCountFrequency (%)
to 432
 
10.0%
residents 329
 
7.6%
priority 304
 
7.1%
or 235
 
5.5%
students 215
 
5.0%
who 195
 
4.5%
attend 165
 
3.8%
an 164
 
3.8%
information 163
 
3.8%
session 162
 
3.8%
Other values (166) 1942
45.1%
2023-12-09T22:21:07.866749image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3885
14.4%
t 2711
10.0%
n 2307
8.5%
o 2279
8.4%
e 2253
8.3%
i 2129
 
7.9%
r 2015
 
7.5%
s 1956
 
7.2%
a 994
 
3.7%
d 953
 
3.5%
Other values (58) 5510
20.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 21272
78.8%
Space Separator 3885
 
14.4%
Uppercase Letter 1584
 
5.9%
Decimal Number 152
 
0.6%
Other Punctuation 49
 
0.2%
Dash Punctuation 20
 
0.1%
Open Punctuation 14
 
0.1%
Close Punctuation 14
 
0.1%
Initial Punctuation 1
 
< 0.1%
Final Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 2711
12.7%
n 2307
10.8%
o 2279
10.7%
e 2253
10.6%
i 2129
10.0%
r 2015
9.5%
s 1956
9.2%
a 994
 
4.7%
d 953
 
4.5%
y 573
 
2.7%
Other values (15) 3102
14.6%
Uppercase Letter
ValueCountFrequency (%)
P 308
19.4%
Y 174
11.0%
N 174
11.0%
C 160
10.1%
B 131
8.3%
O 120
 
7.6%
S 109
 
6.9%
L 72
 
4.5%
E 62
 
3.9%
A 45
 
2.8%
Other values (10) 229
14.5%
Decimal Number
ValueCountFrequency (%)
8 76
50.0%
1 19
 
12.5%
2 18
 
11.8%
6 9
 
5.9%
3 8
 
5.3%
5 8
 
5.3%
0 6
 
3.9%
4 4
 
2.6%
9 2
 
1.3%
7 2
 
1.3%
Other Punctuation
ValueCountFrequency (%)
. 26
53.1%
, 8
 
16.3%
; 5
 
10.2%
/ 4
 
8.2%
& 2
 
4.1%
: 2
 
4.1%
% 2
 
4.1%
Space Separator
ValueCountFrequency (%)
3885
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 22856
84.7%
Common 4136
 
15.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 2711
11.9%
n 2307
10.1%
o 2279
10.0%
e 2253
9.9%
i 2129
9.3%
r 2015
8.8%
s 1956
8.6%
a 994
 
4.3%
d 953
 
4.2%
y 573
 
2.5%
Other values (35) 4686
20.5%
Common
ValueCountFrequency (%)
3885
93.9%
8 76
 
1.8%
. 26
 
0.6%
- 20
 
0.5%
1 19
 
0.5%
2 18
 
0.4%
( 14
 
0.3%
) 14
 
0.3%
6 9
 
0.2%
3 8
 
0.2%
Other values (13) 47
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26990
> 99.9%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3885
14.4%
t 2711
10.0%
n 2307
8.5%
o 2279
8.4%
e 2253
8.3%
i 2129
 
7.9%
r 2015
 
7.5%
s 1956
 
7.2%
a 994
 
3.7%
d 953
 
3.5%
Other values (56) 5508
20.4%
Punctuation
ValueCountFrequency (%)
1
50.0%
1
50.0%

second_priority02
Text

MISSING 

Distinct60
Distinct (%)17.8%
Missing84
Missing (%)19.9%
Memory size40.2 KiB
2023-12-09T22:21:08.141936image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length330
Median length267
Mean length56.38461538
Min length31

Characters and Unicode

Total characters19058
Distinct characters67
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)13.6%

Sample

1st rowThen to Manhattan students or residents who attend an information session
2nd rowFor M35B only: Open only to students whose home language is Chinese (Mandarin)
3rd rowThen to New York City residents
4th rowThen to Manhattan students or residents
5th rowThen to New York City residents
ValueCountFrequency (%)
to 365
 
11.1%
residents 324
 
9.8%
then 317
 
9.6%
new 235
 
7.1%
york 235
 
7.1%
city 235
 
7.1%
who 182
 
5.5%
attend 162
 
4.9%
an 162
 
4.9%
information 162
 
4.9%
Other values (146) 919
27.9%
2023-12-09T22:21:08.594433image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2960
15.5%
e 1860
9.8%
n 1831
9.6%
t 1828
9.6%
o 1588
8.3%
s 1456
 
7.6%
i 1260
 
6.6%
r 1048
 
5.5%
a 686
 
3.6%
d 684
 
3.6%
Other values (57) 3857
20.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 14643
76.8%
Space Separator 2960
 
15.5%
Uppercase Letter 1266
 
6.6%
Decimal Number 112
 
0.6%
Other Punctuation 72
 
0.4%
Close Punctuation 3
 
< 0.1%
Open Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1860
12.7%
n 1831
12.5%
t 1828
12.5%
o 1588
10.8%
s 1456
9.9%
i 1260
8.6%
r 1048
7.2%
a 686
 
4.7%
d 684
 
4.7%
h 578
 
3.9%
Other values (14) 1824
12.5%
Uppercase Letter
ValueCountFrequency (%)
T 318
25.1%
C 240
19.0%
Y 235
18.6%
N 235
18.6%
B 44
 
3.5%
P 31
 
2.4%
D 26
 
2.1%
F 22
 
1.7%
M 20
 
1.6%
Q 20
 
1.6%
Other values (14) 75
 
5.9%
Decimal Number
ValueCountFrequency (%)
2 22
19.6%
1 21
18.8%
8 15
13.4%
5 13
11.6%
3 12
10.7%
6 10
8.9%
0 6
 
5.4%
9 5
 
4.5%
4 5
 
4.5%
7 3
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 29
40.3%
: 21
29.2%
, 17
23.6%
; 3
 
4.2%
& 1
 
1.4%
' 1
 
1.4%
Space Separator
ValueCountFrequency (%)
2960
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 15909
83.5%
Common 3149
 
16.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1860
11.7%
n 1831
11.5%
t 1828
11.5%
o 1588
10.0%
s 1456
9.2%
i 1260
7.9%
r 1048
 
6.6%
a 686
 
4.3%
d 684
 
4.3%
h 578
 
3.6%
Other values (38) 3090
19.4%
Common
ValueCountFrequency (%)
2960
94.0%
. 29
 
0.9%
2 22
 
0.7%
: 21
 
0.7%
1 21
 
0.7%
, 17
 
0.5%
8 15
 
0.5%
5 13
 
0.4%
3 12
 
0.4%
6 10
 
0.3%
Other values (9) 29
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19058
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2960
15.5%
e 1860
9.8%
n 1831
9.6%
t 1828
9.6%
o 1588
8.3%
s 1456
 
7.6%
i 1260
 
6.6%
r 1048
 
5.5%
a 686
 
3.6%
d 684
 
3.6%
Other values (57) 3857
20.2%

third_priority03
Text

MISSING 

Distinct31
Distinct (%)13.5%
Missing193
Missing (%)45.7%
Memory size30.1 KiB
2023-12-09T22:21:08.853951image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length369
Median length236
Mean length49.93886463
Min length31

Characters and Unicode

Total characters11436
Distinct characters65
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)8.7%

Sample

1st rowThen to New York City residents who attend an information session
2nd rowThen to New York City residents
3rd rowThen to New York City residents who attend an information session
4th rowThen to New York City residents who attend an information session
5th rowThen to New York City residents who attend an information session
ValueCountFrequency (%)
to 240
 
12.3%
residents 217
 
11.1%
then 213
 
10.9%
students 157
 
8.0%
or 134
 
6.8%
new 84
 
4.3%
york 84
 
4.3%
city 84
 
4.3%
who 64
 
3.3%
bronx 56
 
2.9%
Other values (98) 624
31.9%
2023-12-09T22:21:09.294788image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1728
15.1%
e 1194
10.4%
n 1116
9.8%
t 1116
9.8%
s 953
8.3%
o 936
8.2%
r 720
 
6.3%
i 563
 
4.9%
d 484
 
4.2%
h 346
 
3.0%
Other values (55) 2280
19.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8858
77.5%
Space Separator 1728
 
15.1%
Uppercase Letter 730
 
6.4%
Other Punctuation 58
 
0.5%
Decimal Number 45
 
0.4%
Close Punctuation 10
 
0.1%
Open Punctuation 7
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1194
13.5%
n 1116
12.6%
t 1116
12.6%
s 953
10.8%
o 936
10.6%
r 720
8.1%
i 563
6.4%
d 484
5.5%
h 346
 
3.9%
a 319
 
3.6%
Other values (14) 1111
12.5%
Uppercase Letter
ValueCountFrequency (%)
T 214
29.3%
B 93
12.7%
C 89
12.2%
N 85
 
11.6%
Y 84
 
11.5%
F 27
 
3.7%
Q 23
 
3.2%
M 23
 
3.2%
P 17
 
2.3%
Z 15
 
2.1%
Other values (13) 60
 
8.2%
Decimal Number
ValueCountFrequency (%)
5 10
22.2%
1 6
13.3%
2 6
13.3%
0 6
13.3%
4 5
11.1%
3 3
 
6.7%
6 3
 
6.7%
9 3
 
6.7%
8 2
 
4.4%
7 1
 
2.2%
Other Punctuation
ValueCountFrequency (%)
: 25
43.1%
. 20
34.5%
; 7
 
12.1%
% 4
 
6.9%
, 2
 
3.4%
Space Separator
ValueCountFrequency (%)
1728
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9588
83.8%
Common 1848
 
16.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1194
12.5%
n 1116
11.6%
t 1116
11.6%
s 953
9.9%
o 936
9.8%
r 720
 
7.5%
i 563
 
5.9%
d 484
 
5.0%
h 346
 
3.6%
a 319
 
3.3%
Other values (37) 1841
19.2%
Common
ValueCountFrequency (%)
1728
93.5%
: 25
 
1.4%
. 20
 
1.1%
5 10
 
0.5%
) 10
 
0.5%
; 7
 
0.4%
( 7
 
0.4%
1 6
 
0.3%
2 6
 
0.3%
0 6
 
0.3%
Other values (8) 23
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11436
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1728
15.1%
e 1194
10.4%
n 1116
9.8%
t 1116
9.8%
s 953
8.3%
o 936
8.2%
r 720
 
6.3%
i 563
 
4.9%
d 484
 
4.2%
h 346
 
3.0%
Other values (55) 2280
19.9%

fourth_priority04
Text

MISSING 

Distinct24
Distinct (%)14.5%
Missing257
Missing (%)60.9%
Memory size23.4 KiB
2023-12-09T22:21:09.551761image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length300
Median length31
Mean length37.67272727
Min length31

Characters and Unicode

Total characters6216
Distinct characters58
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)9.7%

Sample

1st rowThen to Manhattan students or residents
2nd rowThen to District 3 students or residents
3rd rowThen to Districts 1 and 2 students or residents
4th rowThen to Districts 1 and 2 students or residents
5th rowThen to Manhattan students or residents
ValueCountFrequency (%)
to 168
14.6%
then 163
14.1%
residents 161
14.0%
new 129
11.2%
york 129
11.2%
city 129
11.2%
students 40
 
3.5%
or 33
 
2.9%
bronx 14
 
1.2%
who 14
 
1.2%
Other values (70) 174
15.1%
2023-12-09T22:21:09.949704image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
989
15.9%
e 728
11.7%
t 612
9.8%
n 475
 
7.6%
s 461
 
7.4%
o 430
 
6.9%
r 388
 
6.2%
i 367
 
5.9%
d 232
 
3.7%
h 201
 
3.2%
Other values (48) 1333
21.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4568
73.5%
Space Separator 989
 
15.9%
Uppercase Letter 612
 
9.8%
Decimal Number 31
 
0.5%
Other Punctuation 15
 
0.2%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 728
15.9%
t 612
13.4%
n 475
10.4%
s 461
10.1%
o 430
9.4%
r 388
8.5%
i 367
8.0%
d 232
 
5.1%
h 201
 
4.4%
w 148
 
3.2%
Other values (14) 526
11.5%
Uppercase Letter
ValueCountFrequency (%)
T 163
26.6%
C 130
21.2%
Y 129
21.1%
N 129
21.1%
B 18
 
2.9%
D 10
 
1.6%
S 6
 
1.0%
F 6
 
1.0%
M 5
 
0.8%
P 3
 
0.5%
Other values (9) 13
 
2.1%
Decimal Number
ValueCountFrequency (%)
2 7
22.6%
6 5
16.1%
1 5
16.1%
3 5
16.1%
5 4
12.9%
8 1
 
3.2%
4 1
 
3.2%
9 1
 
3.2%
7 1
 
3.2%
0 1
 
3.2%
Other Punctuation
ValueCountFrequency (%)
. 6
40.0%
: 5
33.3%
, 4
26.7%
Space Separator
ValueCountFrequency (%)
989
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5180
83.3%
Common 1036
 
16.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 728
14.1%
t 612
11.8%
n 475
9.2%
s 461
8.9%
o 430
 
8.3%
r 388
 
7.5%
i 367
 
7.1%
d 232
 
4.5%
h 201
 
3.9%
T 163
 
3.1%
Other values (33) 1123
21.7%
Common
ValueCountFrequency (%)
989
95.5%
2 7
 
0.7%
. 6
 
0.6%
6 5
 
0.5%
: 5
 
0.5%
1 5
 
0.5%
3 5
 
0.5%
5 4
 
0.4%
, 4
 
0.4%
8 1
 
0.1%
Other values (5) 5
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6216
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
989
15.9%
e 728
11.7%
t 612
9.8%
n 475
 
7.6%
s 461
 
7.4%
o 430
 
6.9%
r 388
 
6.2%
i 367
 
5.9%
d 232
 
3.7%
h 201
 
3.2%
Other values (48) 1333
21.4%

fifth_priority05
Text

MISSING 

Distinct10
Distinct (%)25.0%
Missing382
Missing (%)90.5%
Memory size15.6 KiB
2023-12-09T22:21:10.165146image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length53
Median length31
Mean length34.825
Min length31

Characters and Unicode

Total characters1393
Distinct characters35
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)15.0%

Sample

1st rowThen to New York City residents
2nd rowThen to Manhattan students or residents
3rd rowThen to Manhattan students or residents
4th rowThen to Manhattan students or residents
5th rowThen to New York City residents
ValueCountFrequency (%)
then 40
15.9%
to 40
15.9%
residents 40
15.9%
new 23
9.2%
york 23
9.2%
city 23
9.2%
students 17
6.8%
or 17
6.8%
brooklyn 7
 
2.8%
manhattan 3
 
1.2%
Other values (14) 18
7.2%
2023-12-09T22:21:10.504836image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
211
15.1%
e 164
11.8%
t 151
10.8%
s 122
8.8%
n 115
8.3%
o 95
 
6.8%
r 92
 
6.6%
i 71
 
5.1%
d 60
 
4.3%
h 43
 
3.1%
Other values (25) 269
19.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1038
74.5%
Space Separator 211
 
15.1%
Uppercase Letter 126
 
9.0%
Decimal Number 15
 
1.1%
Other Punctuation 2
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 164
15.8%
t 151
14.5%
s 122
11.8%
n 115
11.1%
o 95
9.2%
r 92
8.9%
i 71
6.8%
d 60
 
5.8%
h 43
 
4.1%
k 30
 
2.9%
Other values (7) 95
9.2%
Uppercase Letter
ValueCountFrequency (%)
T 40
31.7%
Y 23
18.3%
C 23
18.3%
N 23
18.3%
B 8
 
6.3%
D 4
 
3.2%
M 3
 
2.4%
Q 2
 
1.6%
Decimal Number
ValueCountFrequency (%)
2 6
40.0%
3 2
 
13.3%
1 2
 
13.3%
7 2
 
13.3%
4 1
 
6.7%
0 1
 
6.7%
8 1
 
6.7%
Space Separator
ValueCountFrequency (%)
211
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1164
83.6%
Common 229
 
16.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 164
14.1%
t 151
13.0%
s 122
10.5%
n 115
9.9%
o 95
8.2%
r 92
7.9%
i 71
 
6.1%
d 60
 
5.2%
h 43
 
3.7%
T 40
 
3.4%
Other values (15) 211
18.1%
Common
ValueCountFrequency (%)
211
92.1%
2 6
 
2.6%
, 2
 
0.9%
3 2
 
0.9%
1 2
 
0.9%
7 2
 
0.9%
) 1
 
0.4%
4 1
 
0.4%
0 1
 
0.4%
8 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1393
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
211
15.1%
e 164
11.8%
t 151
10.8%
s 122
8.8%
n 115
8.3%
o 95
 
6.8%
r 92
 
6.6%
i 71
 
5.1%
d 60
 
4.3%
h 43
 
3.1%
Other values (25) 269
19.3%

sixth_priority06
Text

MISSING 

Distinct5
Distinct (%)27.8%
Missing404
Missing (%)95.7%
Memory size14.3 KiB
2023-12-09T22:21:10.705674image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length39
Median length31
Mean length31.72222222
Min length17

Characters and Unicode

Total characters571
Distinct characters28
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)16.7%

Sample

1st rowThen to New York City residents
2nd rowThen to New York City residents
3rd rowThen to New York City residents
4th rowThen to Manhattan students or residents
5th row2. For Y72B only:
ValueCountFrequency (%)
then 17
16.0%
to 17
16.0%
residents 17
16.0%
new 13
12.3%
york 13
12.3%
city 13
12.3%
students 4
 
3.8%
or 4
 
3.8%
brooklyn 2
 
1.9%
manhattan 1
 
0.9%
Other values (5) 5
 
4.7%
2023-12-09T22:21:11.023729image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
88
15.4%
e 70
12.3%
t 57
10.0%
n 44
 
7.7%
s 43
 
7.5%
o 40
 
7.0%
r 37
 
6.5%
i 30
 
5.3%
d 21
 
3.7%
h 18
 
3.2%
Other values (18) 123
21.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 415
72.7%
Space Separator 88
 
15.4%
Uppercase Letter 63
 
11.0%
Decimal Number 3
 
0.5%
Other Punctuation 2
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 70
16.9%
t 57
13.7%
n 44
10.6%
s 43
10.4%
o 40
9.6%
r 37
8.9%
i 30
7.2%
d 21
 
5.1%
h 18
 
4.3%
y 16
 
3.9%
Other values (5) 39
9.4%
Uppercase Letter
ValueCountFrequency (%)
T 17
27.0%
Y 14
22.2%
C 13
20.6%
N 13
20.6%
B 3
 
4.8%
M 1
 
1.6%
F 1
 
1.6%
Q 1
 
1.6%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
7 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
: 1
50.0%
Space Separator
ValueCountFrequency (%)
88
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 478
83.7%
Common 93
 
16.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 70
14.6%
t 57
11.9%
n 44
9.2%
s 43
9.0%
o 40
 
8.4%
r 37
 
7.7%
i 30
 
6.3%
d 21
 
4.4%
h 18
 
3.8%
T 17
 
3.6%
Other values (13) 101
21.1%
Common
ValueCountFrequency (%)
88
94.6%
2 2
 
2.2%
. 1
 
1.1%
7 1
 
1.1%
: 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 571
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
88
15.4%
e 70
12.3%
t 57
10.0%
n 44
 
7.7%
s 43
 
7.5%
o 40
 
7.0%
r 37
 
6.5%
i 30
 
5.3%
d 21
 
3.7%
h 18
 
3.2%
Other values (18) 123
21.5%

seventh_priority07
Text

MISSING 

Distinct2
Distinct (%)40.0%
Missing417
Missing (%)98.8%
Memory size13.6 KiB
2023-12-09T22:21:11.218786image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length37
Median length31
Mean length32.2
Min length31

Characters and Unicode

Total characters161
Distinct characters24
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)20.0%

Sample

1st rowThen to New York City residents
2nd rowa) Priority to continuing 8th graders
3rd rowThen to New York City residents
4th rowThen to New York City residents
5th rowThen to New York City residents
ValueCountFrequency (%)
to 5
16.7%
then 4
13.3%
new 4
13.3%
york 4
13.3%
city 4
13.3%
residents 4
13.3%
a 1
 
3.3%
priority 1
 
3.3%
continuing 1
 
3.3%
8th 1
 
3.3%
2023-12-09T22:21:11.541191image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25
15.5%
e 17
10.6%
t 16
9.9%
r 12
 
7.5%
i 12
 
7.5%
n 11
 
6.8%
o 11
 
6.8%
s 9
 
5.6%
h 5
 
3.1%
d 5
 
3.1%
Other values (14) 38
23.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 117
72.7%
Space Separator 25
 
15.5%
Uppercase Letter 17
 
10.6%
Close Punctuation 1
 
0.6%
Decimal Number 1
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 17
14.5%
t 16
13.7%
r 12
10.3%
i 12
10.3%
n 11
9.4%
o 11
9.4%
s 9
7.7%
h 5
 
4.3%
d 5
 
4.3%
y 5
 
4.3%
Other values (6) 14
12.0%
Uppercase Letter
ValueCountFrequency (%)
T 4
23.5%
C 4
23.5%
Y 4
23.5%
N 4
23.5%
P 1
 
5.9%
Space Separator
ValueCountFrequency (%)
25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Decimal Number
ValueCountFrequency (%)
8 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 134
83.2%
Common 27
 
16.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 17
12.7%
t 16
11.9%
r 12
 
9.0%
i 12
 
9.0%
n 11
 
8.2%
o 11
 
8.2%
s 9
 
6.7%
h 5
 
3.7%
d 5
 
3.7%
y 5
 
3.7%
Other values (11) 31
23.1%
Common
ValueCountFrequency (%)
25
92.6%
) 1
 
3.7%
8 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 161
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25
15.5%
e 17
10.6%
t 16
9.9%
r 12
 
7.5%
i 12
 
7.5%
n 11
 
6.8%
o 11
 
6.8%
s 9
 
5.6%
h 5
 
3.1%
d 5
 
3.1%
Other values (14) 38
23.6%

eighth_priority08
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing421
Missing (%)99.8%
Memory size13.4 KiB
2023-12-09T22:21:12.065150image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length72
Median length72
Mean length72
Min length72

Characters and Unicode

Total characters72
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowb) Then to Bronx students or residents who attend an information session
ValueCountFrequency (%)
b 1
8.3%
then 1
8.3%
to 1
8.3%
bronx 1
8.3%
students 1
8.3%
or 1
8.3%
residents 1
8.3%
who 1
8.3%
attend 1
8.3%
an 1
8.3%
Other values (2) 2
16.7%
2023-12-09T22:21:12.397690image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11
15.3%
n 9
12.5%
t 7
9.7%
o 7
9.7%
s 7
9.7%
e 6
8.3%
r 4
 
5.6%
i 4
 
5.6%
d 3
 
4.2%
a 3
 
4.2%
Other values (10) 11
15.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 58
80.6%
Space Separator 11
 
15.3%
Uppercase Letter 2
 
2.8%
Close Punctuation 1
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 9
15.5%
t 7
12.1%
o 7
12.1%
s 7
12.1%
e 6
10.3%
r 4
6.9%
i 4
6.9%
d 3
 
5.2%
a 3
 
5.2%
h 2
 
3.4%
Other values (6) 6
10.3%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
T 1
50.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 60
83.3%
Common 12
 
16.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 9
15.0%
t 7
11.7%
o 7
11.7%
s 7
11.7%
e 6
10.0%
r 4
6.7%
i 4
6.7%
d 3
 
5.0%
a 3
 
5.0%
h 2
 
3.3%
Other values (8) 8
13.3%
Common
ValueCountFrequency (%)
11
91.7%
) 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 72
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11
15.3%
n 9
12.5%
t 7
9.7%
o 7
9.7%
s 7
9.7%
e 6
8.3%
r 4
 
5.6%
i 4
 
5.6%
d 3
 
4.2%
a 3
 
4.2%
Other values (10) 11
15.3%

ninth_priority09
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing421
Missing (%)99.8%
Memory size13.4 KiB
2023-12-09T22:21:12.607102image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length68
Median length68
Mean length68
Min length68

Characters and Unicode

Total characters68
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowc) Then to New York City residents who attend an information session
ValueCountFrequency (%)
c 1
8.3%
then 1
8.3%
to 1
8.3%
new 1
8.3%
york 1
8.3%
city 1
8.3%
residents 1
8.3%
who 1
8.3%
attend 1
8.3%
an 1
8.3%
Other values (2) 2
16.7%
2023-12-09T22:21:12.945518image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11
16.2%
n 7
10.3%
e 6
8.8%
t 6
8.8%
o 6
8.8%
i 5
 
7.4%
s 5
 
7.4%
a 3
 
4.4%
r 3
 
4.4%
h 2
 
2.9%
Other values (12) 14
20.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 52
76.5%
Space Separator 11
 
16.2%
Uppercase Letter 4
 
5.9%
Close Punctuation 1
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 7
13.5%
e 6
11.5%
t 6
11.5%
o 6
11.5%
i 5
9.6%
s 5
9.6%
a 3
5.8%
r 3
5.8%
h 2
 
3.8%
w 2
 
3.8%
Other values (6) 7
13.5%
Uppercase Letter
ValueCountFrequency (%)
Y 1
25.0%
C 1
25.0%
N 1
25.0%
T 1
25.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 56
82.4%
Common 12
 
17.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 7
12.5%
e 6
10.7%
t 6
10.7%
o 6
10.7%
i 5
8.9%
s 5
8.9%
a 3
 
5.4%
r 3
 
5.4%
h 2
 
3.6%
w 2
 
3.6%
Other values (10) 11
19.6%
Common
ValueCountFrequency (%)
11
91.7%
) 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 68
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11
16.2%
n 7
10.3%
e 6
8.8%
t 6
8.8%
o 6
8.8%
i 5
 
7.4%
s 5
 
7.4%
a 3
 
4.4%
r 3
 
4.4%
h 2
 
2.9%
Other values (12) 14
20.6%

tenth_priority10
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing421
Missing (%)99.8%
Memory size13.4 KiB
2023-12-09T22:21:13.142487image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length74
Median length74
Mean length74
Min length74

Characters and Unicode

Total characters74
Distinct characters22
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowd) Then to Bronx students or residents, e) Then to New York City residents
ValueCountFrequency (%)
then 2
14.3%
to 2
14.3%
residents 2
14.3%
d 1
7.1%
bronx 1
7.1%
students 1
7.1%
or 1
7.1%
e 1
7.1%
new 1
7.1%
york 1
7.1%
2023-12-09T22:21:13.459268image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13
17.6%
e 9
12.2%
t 7
9.5%
n 6
8.1%
s 6
8.1%
o 5
 
6.8%
r 5
 
6.8%
d 4
 
5.4%
i 3
 
4.1%
T 2
 
2.7%
Other values (12) 14
18.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 52
70.3%
Space Separator 13
 
17.6%
Uppercase Letter 6
 
8.1%
Close Punctuation 2
 
2.7%
Other Punctuation 1
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 9
17.3%
t 7
13.5%
n 6
11.5%
s 6
11.5%
o 5
9.6%
r 5
9.6%
d 4
7.7%
i 3
 
5.8%
h 2
 
3.8%
w 1
 
1.9%
Other values (4) 4
7.7%
Uppercase Letter
ValueCountFrequency (%)
T 2
33.3%
C 1
16.7%
Y 1
16.7%
N 1
16.7%
B 1
16.7%
Space Separator
ValueCountFrequency (%)
13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 58
78.4%
Common 16
 
21.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 9
15.5%
t 7
12.1%
n 6
10.3%
s 6
10.3%
o 5
8.6%
r 5
8.6%
d 4
6.9%
i 3
 
5.2%
T 2
 
3.4%
h 2
 
3.4%
Other values (9) 9
15.5%
Common
ValueCountFrequency (%)
13
81.2%
) 2
 
12.5%
, 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 74
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13
17.6%
e 9
12.2%
t 7
9.5%
n 6
8.1%
s 6
8.1%
o 5
 
6.8%
r 5
 
6.8%
d 4
 
5.4%
i 3
 
4.1%
T 2
 
2.7%
Other values (12) 14
18.9%

eleventh_priority11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing422
Missing (%)100.0%
Memory size3.4 KiB
Distinct10
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
2023-12-09T22:21:13.586276image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.002369668
Min length1

Characters and Unicode

Total characters423
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row1
2nd row3
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 316
74.9%
2 40
 
9.5%
3 19
 
4.5%
4 17
 
4.0%
5 9
 
2.1%
6 7
 
1.7%
8 6
 
1.4%
7 5
 
1.2%
9 2
 
0.5%
10 1
 
0.2%
2023-12-09T22:21:13.823546image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 317
74.9%
2 40
 
9.5%
3 19
 
4.5%
4 17
 
4.0%
5 9
 
2.1%
6 7
 
1.7%
8 6
 
1.4%
7 5
 
1.2%
9 2
 
0.5%
0 1
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 423
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 317
74.9%
2 40
 
9.5%
3 19
 
4.5%
4 17
 
4.0%
5 9
 
2.1%
6 7
 
1.7%
8 6
 
1.4%
7 5
 
1.2%
9 2
 
0.5%
0 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 423
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 317
74.9%
2 40
 
9.5%
3 19
 
4.5%
4 17
 
4.0%
5 9
 
2.1%
6 7
 
1.7%
8 6
 
1.4%
7 5
 
1.2%
9 2
 
0.5%
0 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 423
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 317
74.9%
2 40
 
9.5%
3 19
 
4.5%
4 17
 
4.0%
5 9
 
2.1%
6 7
 
1.7%
8 6
 
1.4%
7 5
 
1.2%
9 2
 
0.5%
0 1
 
0.2%

email
Text

MISSING 

Distinct360
Distinct (%)100.0%
Missing62
Missing (%)14.7%
Memory size30.4 KiB
2023-12-09T22:21:14.105218image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length47
Median length37
Mean length23.52777778
Min length10

Characters and Unicode

Total characters8470
Distinct characters69
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique360 ?
Unique (%)100.0%

Sample

1st rowcloughl@schools.nyc.gov
2nd row01M448@schools.nyc.gov
3rd rowtomm@eschs.org
4th rowmfortun@schools.nyc.gov
5th rowSglasgall@schools.nyc.gov
ValueCountFrequency (%)
contact 2
 
0.5%
79x682@schools.nyc.gov 1
 
0.3%
azambra@schools.nyc.gov 1
 
0.3%
dsilva3@schools.nyc.gov 1
 
0.3%
jgriffiths@schools.nyc.gov 1
 
0.3%
acastro3@schools.nyc.gov 1
 
0.3%
minbal@schools.nyc.gov 1
 
0.3%
hhall3@schools.nyc.gov 1
 
0.3%
10x237@schools.nyc.gov 1
 
0.3%
19k615@schools.nyc.gov 1
 
0.3%
Other values (359) 359
97.0%
2023-12-09T22:21:14.549016image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 1113
 
13.1%
s 735
 
8.7%
c 689
 
8.1%
. 605
 
7.1%
n 504
 
6.0%
l 460
 
5.4%
g 417
 
4.9%
h 397
 
4.7%
@ 357
 
4.2%
a 350
 
4.1%
Other values (59) 2843
33.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6989
82.5%
Other Punctuation 964
 
11.4%
Decimal Number 315
 
3.7%
Uppercase Letter 181
 
2.1%
Space Separator 10
 
0.1%
Dash Punctuation 7
 
0.1%
Connector Punctuation 2
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1113
15.9%
s 735
10.5%
c 689
9.9%
n 504
 
7.2%
l 460
 
6.6%
g 417
 
6.0%
h 397
 
5.7%
a 350
 
5.0%
y 312
 
4.5%
e 291
 
4.2%
Other values (16) 1721
24.6%
Uppercase Letter
ValueCountFrequency (%)
S 18
 
9.9%
K 18
 
9.9%
M 14
 
7.7%
R 12
 
6.6%
Q 12
 
6.6%
A 11
 
6.1%
C 10
 
5.5%
H 10
 
5.5%
F 8
 
4.4%
G 8
 
4.4%
Other values (15) 60
33.1%
Decimal Number
ValueCountFrequency (%)
2 68
21.6%
4 48
15.2%
1 40
12.7%
3 35
11.1%
0 31
9.8%
5 28
8.9%
6 21
 
6.7%
7 17
 
5.4%
8 15
 
4.8%
9 12
 
3.8%
Other Punctuation
ValueCountFrequency (%)
. 605
62.8%
@ 357
37.0%
" 2
 
0.2%
Space Separator
ValueCountFrequency (%)
10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7170
84.7%
Common 1300
 
15.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1113
15.5%
s 735
 
10.3%
c 689
 
9.6%
n 504
 
7.0%
l 460
 
6.4%
g 417
 
5.8%
h 397
 
5.5%
a 350
 
4.9%
y 312
 
4.4%
e 291
 
4.1%
Other values (41) 1902
26.5%
Common
ValueCountFrequency (%)
. 605
46.5%
@ 357
27.5%
2 68
 
5.2%
4 48
 
3.7%
1 40
 
3.1%
3 35
 
2.7%
0 31
 
2.4%
5 28
 
2.2%
6 21
 
1.6%
7 17
 
1.3%
Other values (8) 50
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8470
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 1113
 
13.1%
s 735
 
8.7%
c 689
 
8.1%
. 605
 
7.1%
n 504
 
6.0%
l 460
 
5.4%
g 417
 
4.9%
h 397
 
4.7%
@ 357
 
4.2%
a 350
 
4.1%
Other values (59) 2843
33.6%
Distinct419
Distinct (%)99.5%
Missing1
Missing (%)0.2%
Memory size36.8 KiB
http://www.ywlnetwork.org
 
2
http://www.bard.edu/bhsec
 
2
http://www.belmontprep.org
 
1
http://www.bronxleadershipacademy.org
 
1
http://schools.nyc.gov/schoolportals/17/K531
 
1
Other values (414)
414 
ValueCountFrequency (%)
http://www.ywlnetwork.org 2
 
0.5%
http://www.bard.edu/bhsec 2
 
0.5%
http://www.belmontprep.org 1
 
0.2%
http://www.bronxleadershipacademy.org 1
 
0.2%
http://schools.nyc.gov/schoolportals/17/K531 1
 
0.2%
http://www.csihighschool.org 1
 
0.2%
http://www.leadershipnyc.org 1
 
0.2%
http://www.mecps.org 1
 
0.2%
http://schools.nyc.gov/schoolportals/17/K382 1
 
0.2%
http://schools.nyc.gov/schoolportals/02/M439 1
 
0.2%
Other values (409) 409
96.9%
ValueCountFrequency (%)
http 420
99.5%
https 1
 
0.2%
(Missing) 1
 
0.2%
ValueCountFrequency (%)
schools.nyc.gov 129
30.6%
www.ywlnetwork.org 3
 
0.7%
www.bard.edu 2
 
0.5%
www.citypolyhigh.org 1
 
0.2%
www.BronxleadershipAcademy2.org 1
 
0.2%
www.pelhamprepacademy.org 1
 
0.2%
www.sthnewyork.com 1
 
0.2%
www.academyforwriters.com 1
 
0.2%
www.RockawayParkHS.com 1
 
0.2%
www.brooklynartshs.org 1
 
0.2%
Other values (280) 280
66.4%
ValueCountFrequency (%)
285
67.5%
/ 2
 
0.5%
/bhsec 2
 
0.5%
/schoolportals/21/K337 1
 
0.2%
/schoolportals/28/Q325 1
 
0.2%
/schoolportals/02/M296 1
 
0.2%
/schoolportals/11/X545 1
 
0.2%
/schoolportals/16/K455 1
 
0.2%
/network_schl_astoria.htm 1
 
0.2%
/schoolportals/08/X376 1
 
0.2%
Other values (125) 125
29.6%
ValueCountFrequency (%)
421
99.8%
(Missing) 1
 
0.2%
ValueCountFrequency (%)
421
99.8%
(Missing) 1
 
0.2%

school_type
Text

MISSING 

Distinct9
Distinct (%)10.7%
Missing338
Missing (%)80.1%
Memory size16.5 KiB
2023-12-09T22:21:14.723797image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length32
Median length25
Mean length14.25
Min length10

Characters and Unicode

Total characters1197
Distinct characters28
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)2.4%

Sample

1st rowCTE School
2nd rowAll-Girls School
3rd rowCTE School
4th rowInternational School
5th rowInternational School
ValueCountFrequency (%)
school 85
47.8%
cte 40
22.5%
international 17
 
9.6%
new 16
 
9.0%
specialized 9
 
5.1%
all-girls 8
 
4.5%
all-boys 3
 
1.7%
2023-12-09T22:21:15.014686image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 190
15.9%
l 141
11.8%
94
 
7.9%
S 94
 
7.9%
c 94
 
7.9%
h 85
 
7.1%
e 51
 
4.3%
n 51
 
4.3%
a 43
 
3.6%
i 43
 
3.6%
Other values (18) 311
26.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 814
68.0%
Uppercase Letter 269
 
22.5%
Space Separator 94
 
7.9%
Dash Punctuation 11
 
0.9%
Other Punctuation 9
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 190
23.3%
l 141
17.3%
c 94
11.5%
h 85
10.4%
e 51
 
6.3%
n 51
 
6.3%
a 43
 
5.3%
i 43
 
5.3%
t 34
 
4.2%
r 25
 
3.1%
Other values (6) 57
 
7.0%
Uppercase Letter
ValueCountFrequency (%)
S 94
34.9%
T 40
14.9%
C 40
14.9%
E 40
14.9%
I 17
 
6.3%
N 16
 
5.9%
A 11
 
4.1%
G 8
 
3.0%
B 3
 
1.1%
Space Separator
ValueCountFrequency (%)
94
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1083
90.5%
Common 114
 
9.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 190
17.5%
l 141
13.0%
S 94
 
8.7%
c 94
 
8.7%
h 85
 
7.8%
e 51
 
4.7%
n 51
 
4.7%
a 43
 
4.0%
i 43
 
4.0%
T 40
 
3.7%
Other values (15) 251
23.2%
Common
ValueCountFrequency (%)
94
82.5%
- 11
 
9.6%
, 9
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1197
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 190
15.9%
l 141
11.8%
94
 
7.9%
S 94
 
7.9%
c 94
 
7.9%
h 85
 
7.1%
e 51
 
4.3%
n 51
 
4.3%
a 43
 
3.6%
i 43
 
3.6%
Other values (18) 311
26.0%
Distinct421
Distinct (%)100.0%
Missing1
Missing (%)0.2%
Memory size298.9 KiB
2023-12-09T22:21:15.425042image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1857
Median length701
Mean length620.2304038
Min length65

Characters and Unicode

Total characters261117
Distinct characters79
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique421 ?
Unique (%)100.0%

Sample

1st rowHenry Street School for International Studies is a unique small school founded by Asia Society. While in pursuit of knowledge about other world regions, including their histories, economies and world languages, students simultaneously acquire the knowledge and skills to prepare for college and/or careers. Teachers and other adults who make up the learning community forge supportive relationships with students and parents while providing challenging and engaging learning experiences. Our school partners with various community, arts, and business organizations to help students meet success. Our theme of international studies extends beyond the classroom, where students participate in ongoing “Advisory Day Out” excursions where the multiculturalism of NYC becomes the classroom.
2nd rowWe are a New York University/Department of Education Partnership School that provides students with a challenging curriculum in a supportive environment so they can participate successfully in the academic world and the workforce.
3rd rowWe are a small 6-12 secondary school that prepares all students for college and careers. We set high standards and work with all of our students to help them meet these standards. With no more than 25 students per class, teachers are able to provide personal attention in a respectful environment. Our staff makes sure that we know every student well. We assess our students by challenging them to use what they have learned in creative ways to complete interesting projects. Students, staff, families, and community members all see themselves as part of a team whose main goal is the success of every individual student.
4th rowMarta Valle High School (MVHS) continues the tradition established by our namesake Marta Valle (a social worker, youth advocate and community organizer) by offering a strong academic and character development program in a personalized setting. Our academics are supplemented by a wide range of electives in visual, performing, and culinary arts, video, and music. As an iZone school, our students have the opportunity to earn Advanced Placement credit and take college-level courses for credit at The City University of New York (CUNY). Other opportunities include SAT Prep, Regents Prep, numerous clubs, PSAL, Dance, Capoeira and Weight Training. MVHS is a place where “Educating Hearts and Minds for the 21st Century” is a reality!
5th rowNew Explorations into Science, Technology and Math High School (NEST+m) is a K-12 school that is committed to providing an exemplary accelerated education for students of diverse backgrounds who have the ability and promise to meet the demands of an academically challenging curriculum. The Upper School (grades 9-12) engages students to think abstractly and critically, and encourages them to formulate questions that guide their learning experience via discussions and research. Multiple opportunities exist for students to have internships at various local universities in the sciences and the arts.
ValueCountFrequency (%)
and 2206
 
5.7%
the 1421
 
3.7%
to 1341
 
3.5%
students 1091
 
2.8%
of 1037
 
2.7%
a 987
 
2.5%
in 968
 
2.5%
our 836
 
2.2%
school 663
 
1.7%
for 514
 
1.3%
Other values (3659) 27757
71.5%
2023-12-09T22:21:16.019221image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38406
14.7%
e 25259
 
9.7%
t 17594
 
6.7%
a 16483
 
6.3%
n 16197
 
6.2%
i 15866
 
6.1%
o 15820
 
6.1%
r 14655
 
5.6%
s 14637
 
5.6%
l 10416
 
4.0%
Other values (69) 75784
29.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 211020
80.8%
Space Separator 38406
 
14.7%
Uppercase Letter 5958
 
2.3%
Other Punctuation 4274
 
1.6%
Dash Punctuation 706
 
0.3%
Decimal Number 364
 
0.1%
Close Punctuation 162
 
0.1%
Open Punctuation 162
 
0.1%
Initial Punctuation 32
 
< 0.1%
Final Punctuation 32
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 25259
12.0%
t 17594
 
8.3%
a 16483
 
7.8%
n 16197
 
7.7%
i 15866
 
7.5%
o 15820
 
7.5%
r 14655
 
6.9%
s 14637
 
6.9%
l 10416
 
4.9%
c 9639
 
4.6%
Other values (16) 54454
25.8%
Uppercase Letter
ValueCountFrequency (%)
S 809
13.6%
A 635
 
10.7%
C 530
 
8.9%
T 483
 
8.1%
W 422
 
7.1%
O 405
 
6.8%
E 344
 
5.8%
H 289
 
4.9%
L 232
 
3.9%
P 214
 
3.6%
Other values (15) 1595
26.8%
Other Punctuation
ValueCountFrequency (%)
, 2097
49.1%
. 1823
42.7%
' 159
 
3.7%
/ 54
 
1.3%
: 40
 
0.9%
" 34
 
0.8%
; 21
 
0.5%
& 18
 
0.4%
! 12
 
0.3%
? 12
 
0.3%
Decimal Number
ValueCountFrequency (%)
1 99
27.2%
2 74
20.3%
0 71
19.5%
6 30
 
8.2%
9 26
 
7.1%
5 21
 
5.8%
3 18
 
4.9%
4 17
 
4.7%
8 6
 
1.6%
7 2
 
0.5%
Space Separator
ValueCountFrequency (%)
38406
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 706
100.0%
Close Punctuation
ValueCountFrequency (%)
) 162
100.0%
Open Punctuation
ValueCountFrequency (%)
( 162
100.0%
Initial Punctuation
ValueCountFrequency (%)
32
100.0%
Final Punctuation
ValueCountFrequency (%)
32
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 216978
83.1%
Common 44139
 
16.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 25259
11.6%
t 17594
 
8.1%
a 16483
 
7.6%
n 16197
 
7.5%
i 15866
 
7.3%
o 15820
 
7.3%
r 14655
 
6.8%
s 14637
 
6.7%
l 10416
 
4.8%
c 9639
 
4.4%
Other values (41) 60412
27.8%
Common
ValueCountFrequency (%)
38406
87.0%
, 2097
 
4.8%
. 1823
 
4.1%
- 706
 
1.6%
) 162
 
0.4%
( 162
 
0.4%
' 159
 
0.4%
1 99
 
0.2%
2 74
 
0.2%
0 71
 
0.2%
Other values (18) 380
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 261053
> 99.9%
Punctuation 64
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38406
14.7%
e 25259
 
9.7%
t 17594
 
6.7%
a 16483
 
6.3%
n 16197
 
6.2%
i 15866
 
6.1%
o 15820
 
6.1%
r 14655
 
5.6%
s 14637
 
5.6%
l 10416
 
4.0%
Other values (67) 75720
29.0%
Punctuation
ValueCountFrequency (%)
32
50.0%
32
50.0%
Distinct420
Distinct (%)100.0%
Missing2
Missing (%)0.5%
Memory size170.6 KiB
2023-12-09T22:21:16.415198image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1404
Median length446.5
Mean length355.702381
Min length13

Characters and Unicode

Total characters149395
Distinct characters80
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique420 ?
Unique (%)100.0%

Sample

1st rowGlobal/International Studies in core subjects, Literacy block schedule, Personalized instruction in small classes, Student Advisories, International travel opportunities, After-school program focused on youth leadership
2nd rowCore courses are available in Chinese (Mandarin). Technology courses include: Microsoft Office, Programming C++, Photoshop, Film Production. College Now (10th, 11th, and 12th grades) offered on site and at Baruch College and Borough of Manhattan Community College (BMCC), College Summit. Saturday ESL classes at Saint John's University, Kaplan SAT Prep, Advanced Regents Honors Program, National Honor Society, Resource Center, Peer Tutoring, Deloitte Academy (one-on-one mentoring program)
3rd rowProject-based Learning, Portfolios & Roundtable Presentations, Advisory System, Full-time College Counselor through the College Bound Initiative, and College Now classes at Hunter College. We offer a wide range of interesting elective classes including: Visual Arts, Auto Shop, Cooking, Digital Arts and Photography, Skateboarding, Filmmaking, Chess, Dance, Bicycling
4th rowModel Innovative College and Career Readiness offering an Advanced Regents Diploma. Students may graduate early or earn up to 8 college credits through the College Now Program. College Placement Office, College Advisor, College For Every Student, Peer Leadership, Statistics, Culinary Arts, Video Production, Music Production, Theory and Voice, Piano, Visual Art, Drama, Dance, Advisory, 21st Century Extended Day, Saturday Enrichment/Academic Program, Culinary Arts Kitchen, Fitness and Weight Training Studio, Media Lab, Music Recording, Video Production and Dance Studios. Technology is infused across all disciplines through a Blended Online Instructional Model.
5th row1st level science sequence - 9th grade: Regents Physics with Recitation/Applications and math for Physics courses; 10th grade: Regents Chemistry and 1 term of Computer Science with the option of an Advanced Research class; 11th grade: Living Environment; 12th grade: Options include science electives, AP Biology, AP Chemistry, AP Physics or AP Environmental Science. The 2nd level science sequence is for accelerated students who have demonstrated aptitude for the sciences and mathematics; begins with AP Physics B in 9th grade, AP Chemistry in 10th grade, AP Biology in 11th grade, and AP Environmental Science in 12th grade.
ValueCountFrequency (%)
and 882
 
4.5%
college 647
 
3.3%
in 334
 
1.7%
program 328
 
1.7%
the 296
 
1.5%
of 278
 
1.4%
to 240
 
1.2%
courses 221
 
1.1%
now 209
 
1.1%
science 195
 
1.0%
Other values (2634) 15834
81.4%
2023-12-09T22:21:17.006267image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19044
 
12.7%
e 13426
 
9.0%
n 9232
 
6.2%
i 9052
 
6.1%
r 8894
 
6.0%
o 8684
 
5.8%
a 8668
 
5.8%
t 8016
 
5.4%
s 7493
 
5.0%
l 5584
 
3.7%
Other values (70) 51302
34.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 110373
73.9%
Space Separator 19044
 
12.7%
Uppercase Letter 13093
 
8.8%
Other Punctuation 5225
 
3.5%
Dash Punctuation 472
 
0.3%
Decimal Number 442
 
0.3%
Open Punctuation 365
 
0.2%
Close Punctuation 364
 
0.2%
Math Symbol 14
 
< 0.1%
Initial Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 13426
12.2%
n 9232
 
8.4%
i 9052
 
8.2%
r 8894
 
8.1%
o 8684
 
7.9%
a 8668
 
7.9%
t 8016
 
7.3%
s 7493
 
6.8%
l 5584
 
5.1%
c 4899
 
4.4%
Other values (16) 26425
23.9%
Uppercase Letter
ValueCountFrequency (%)
C 1857
14.2%
A 1514
11.6%
S 1388
10.6%
P 1221
 
9.3%
T 798
 
6.1%
E 743
 
5.7%
M 619
 
4.7%
I 564
 
4.3%
L 513
 
3.9%
N 472
 
3.6%
Other values (16) 3404
26.0%
Other Punctuation
ValueCountFrequency (%)
, 3910
74.8%
; 448
 
8.6%
. 322
 
6.2%
: 213
 
4.1%
& 155
 
3.0%
/ 116
 
2.2%
' 46
 
0.9%
" 9
 
0.2%
@ 3
 
0.1%
! 2
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 176
39.8%
0 67
 
15.2%
2 63
 
14.3%
9 60
 
13.6%
3 23
 
5.2%
4 19
 
4.3%
5 16
 
3.6%
6 9
 
2.0%
8 6
 
1.4%
7 3
 
0.7%
Space Separator
ValueCountFrequency (%)
19044
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 472
100.0%
Open Punctuation
ValueCountFrequency (%)
( 365
100.0%
Close Punctuation
ValueCountFrequency (%)
) 364
100.0%
Math Symbol
ValueCountFrequency (%)
+ 14
100.0%
Initial Punctuation
ValueCountFrequency (%)
2
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 123466
82.6%
Common 25929
 
17.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 13426
 
10.9%
n 9232
 
7.5%
i 9052
 
7.3%
r 8894
 
7.2%
o 8684
 
7.0%
a 8668
 
7.0%
t 8016
 
6.5%
s 7493
 
6.1%
l 5584
 
4.5%
c 4899
 
4.0%
Other values (42) 39518
32.0%
Common
ValueCountFrequency (%)
19044
73.4%
, 3910
 
15.1%
- 472
 
1.8%
; 448
 
1.7%
( 365
 
1.4%
) 364
 
1.4%
. 322
 
1.2%
: 213
 
0.8%
1 176
 
0.7%
& 155
 
0.6%
Other values (18) 460
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 149392
> 99.9%
Punctuation 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19044
 
12.7%
e 13426
 
9.0%
n 9232
 
6.2%
i 9052
 
6.1%
r 8894
 
6.0%
o 8684
 
5.8%
a 8668
 
5.8%
t 8016
 
5.4%
s 7493
 
5.0%
l 5584
 
3.7%
Other values (68) 51299
34.3%
Punctuation
ValueCountFrequency (%)
2
66.7%
1
33.3%

language_classes
Text

MISSING 

Distinct72
Distinct (%)18.4%
Missing30
Missing (%)7.1%
Memory size29.0 KiB
2023-12-09T22:21:17.223650image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length141
Median length7
Mean length15.91581633
Min length5

Characters and Unicode

Total characters6239
Distinct characters42
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)12.8%

Sample

1st rowChinese (Mandarin), Spanish
2nd rowChinese, Spanish
3rd rowBengali, French, Spanish
4th rowChinese (Mandarin), French, German, Latin, Spanish
5th rowChinese (Mandarin), Latin, Spanish
ValueCountFrequency (%)
spanish 376
46.2%
french 107
 
13.1%
chinese 52
 
6.4%
italian 38
 
4.7%
language 35
 
4.3%
latin 31
 
3.8%
mandarin 27
 
3.3%
native 25
 
3.1%
arts 25
 
3.1%
japanese 16
 
2.0%
Other values (17) 82
 
10.1%
2023-12-09T22:21:17.620650image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 768
12.3%
a 718
11.5%
i 600
9.6%
h 541
8.7%
s 501
 
8.0%
422
 
6.8%
p 392
 
6.3%
S 386
 
6.2%
e 365
 
5.9%
, 291
 
4.7%
Other values (32) 1255
20.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4650
74.5%
Uppercase Letter 816
 
13.1%
Space Separator 422
 
6.8%
Other Punctuation 291
 
4.7%
Close Punctuation 29
 
0.5%
Open Punctuation 29
 
0.5%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 768
16.5%
a 718
15.4%
i 600
12.9%
h 541
11.6%
s 501
10.8%
p 392
8.4%
e 365
7.8%
r 208
 
4.5%
c 126
 
2.7%
t 125
 
2.7%
Other values (10) 306
 
6.6%
Uppercase Letter
ValueCountFrequency (%)
S 386
47.3%
F 107
 
13.1%
L 66
 
8.1%
C 59
 
7.2%
A 41
 
5.0%
I 38
 
4.7%
M 31
 
3.8%
N 25
 
3.1%
J 16
 
2.0%
G 16
 
2.0%
Other values (7) 31
 
3.8%
Space Separator
ValueCountFrequency (%)
422
100.0%
Other Punctuation
ValueCountFrequency (%)
, 291
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5466
87.6%
Common 773
 
12.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 768
14.1%
a 718
13.1%
i 600
11.0%
h 541
9.9%
s 501
9.2%
p 392
7.2%
S 386
7.1%
e 365
6.7%
r 208
 
3.8%
c 126
 
2.3%
Other values (27) 861
15.8%
Common
ValueCountFrequency (%)
422
54.6%
, 291
37.6%
) 29
 
3.8%
( 29
 
3.8%
- 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6239
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 768
12.3%
a 718
11.5%
i 600
9.6%
h 541
8.7%
s 501
 
8.0%
422
 
6.8%
p 392
 
6.3%
S 386
 
6.2%
e 365
 
5.9%
, 291
 
4.7%
Other values (32) 1255
20.1%
Distinct252
Distinct (%)82.9%
Missing118
Missing (%)28.0%
Memory size57.9 KiB
2023-12-09T22:21:17.887457image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length693
Median length208
Mean length125.1875
Min length7

Characters and Unicode

Total characters38057
Distinct characters44
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique230 ?
Unique (%)75.7%

Sample

1st rowPsychology
2nd rowCalculus AB, Chinese Language and Culture, English Literature and Composition, Spanish Language, Spanish Literature, United States History, World History
3rd rowCalculus AB, English Literature and Composition
4th rowCalculus AB, English Literature and Composition, Physics B
5th rowBiology, Calculus AB, Calculus BC, Chemistry, Chinese Language and Culture, Computer Science A, Economics: Micro, English Language and Composition, English Literature and Composition, Environmental Science, European History, French Language, German Language, Government and Politics: Comparative, Music Theory, Physics B, Psychology, Spanish Language, Spanish Literature, Statistics, Studio Art: Drawing, United States History, World History
ValueCountFrequency (%)
and 489
 
10.5%
english 354
 
7.6%
composition 354
 
7.6%
language 341
 
7.3%
history 328
 
7.1%
literature 264
 
5.7%
united 248
 
5.3%
states 248
 
5.3%
calculus 209
 
4.5%
spanish 189
 
4.1%
Other values (43) 1627
35.0%
2023-12-09T22:21:18.353448image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4347
 
11.4%
i 3063
 
8.0%
t 2669
 
7.0%
n 2631
 
6.9%
a 2406
 
6.3%
o 2361
 
6.2%
s 2280
 
6.0%
e 2121
 
5.6%
, 1515
 
4.0%
r 1484
 
3.9%
Other values (34) 13180
34.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 27587
72.5%
Uppercase Letter 4376
 
11.5%
Space Separator 4347
 
11.4%
Other Punctuation 1711
 
4.5%
Dash Punctuation 18
 
< 0.1%
Decimal Number 18
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 3063
11.1%
t 2669
9.7%
n 2631
9.5%
a 2406
 
8.7%
o 2361
 
8.6%
s 2280
 
8.3%
e 2121
 
7.7%
r 1484
 
5.4%
g 1280
 
4.6%
l 1245
 
4.5%
Other values (9) 6047
21.9%
Uppercase Letter
ValueCountFrequency (%)
C 811
18.5%
S 614
14.0%
L 609
13.9%
E 500
11.4%
B 395
9.0%
H 348
8.0%
A 253
 
5.8%
U 248
 
5.7%
P 203
 
4.6%
G 111
 
2.5%
Other values (9) 284
 
6.5%
Other Punctuation
ValueCountFrequency (%)
, 1515
88.5%
: 196
 
11.5%
Decimal Number
ValueCountFrequency (%)
2 12
66.7%
3 6
33.3%
Space Separator
ValueCountFrequency (%)
4347
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 31963
84.0%
Common 6094
 
16.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 3063
 
9.6%
t 2669
 
8.4%
n 2631
 
8.2%
a 2406
 
7.5%
o 2361
 
7.4%
s 2280
 
7.1%
e 2121
 
6.6%
r 1484
 
4.6%
g 1280
 
4.0%
l 1245
 
3.9%
Other values (28) 10423
32.6%
Common
ValueCountFrequency (%)
4347
71.3%
, 1515
 
24.9%
: 196
 
3.2%
- 18
 
0.3%
2 12
 
0.2%
3 6
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38057
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4347
 
11.4%
i 3063
 
8.0%
t 2669
 
7.0%
n 2631
 
6.9%
a 2406
 
6.3%
o 2361
 
6.2%
s 2280
 
6.0%
e 2121
 
5.6%
, 1515
 
4.0%
r 1484
 
3.9%
Other values (34) 13180
34.6%
Distinct420
Distinct (%)100.0%
Missing2
Missing (%)0.5%
Memory size166.6 KiB
2023-12-09T22:21:18.770242image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1244
Median length444.5
Mean length345.5857143
Min length27

Characters and Unicode

Total characters145146
Distinct characters78
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique420 ?
Unique (%)100.0%

Sample

1st rowMath through Card Play, Poetry Club, Drama Club, Big Brothers/Big Sisters, Student Government, Future Project
2nd rowBasketball, Badminton, Handball, Dance, Fitness Club, Ping-Pong, Tennis, Step Team, After-School tutoring, Peer Tutoring, Lunchtime Saturday SAT Prep, Regents Prep, National Honor Society, Council for Unity, Young Women's Empowerment, Student Assistance Services, Aviation Club (fly a real plane across the Long Island Sound), Board Games, Book Club, Chess, Robotics, Computer Club, Spanish Club, Student Government, Art Club, Audio Club at a live radio station, Music Club, Chorus, Digital Art Studio, Guitar and Piano, Literary Magazine, Murals and School Beautification, Video Club
3rd rowAfter-School Tutoring, Art Portfolio Classes, Chess Team, I Challenge Myself Bicycling Program, Dance, Environmental Committee, Gay/Straight Alliance, Graphic Novel Club, Hip-Hop Beat Making & Rhyming, Model UN, School Newspaper, Peer Tutoring, Principal's Book Club, Rock Band Program, SAT Prep Classes, Scholars Program, School Newspaper, Skateboarding PE Classes, Student Council, Choir, Travel Club, Volleyball, Wall Street Wizards, Saturday Photography Program
4th rowModel Peer Leadership Program, "The Vine" Student Newsletter, 21st Century After-school Program, Student Ambassadors, Animation, Annual College and Career Fair, Monthly College Tours, Annual Family Night, Art, Audio Recording, Break Dancing, Camping, Theater Trips, Capoiera, Cents Ability, Cheerleading, Chorus, College Courses, College Office, College Trips & Tours, Culinary Arts, CUNY and Free Application for Federal Student Aid (FAFSA) Application Workshops, Dance, Film, Gallatin Great Works Project (NYU), Jewelry Making, Kaplan SAT Prep, Monthly Family Resource Fairs, MOUSE Squad, Music Recording and Engineering, National Honor Society, New York University (NYU), Empire State College, Placement and Referral Office on site for Summer Youth Employment Program, Parent Resource Room, Publicolor, Painting, Peer Mediation and Conflict Resolution, Piano, Ping-Pong, Princeton Center for Leadership, Recyling, Rock Band, Saturday Success Academy Regents Prep, Smart and Fabulous Fashion Show, Songwriting, Step Dance, Student Advisory Council, Student Ambassador Program, Sarah Lawrence College Student Interns, Cafe Clubs (during lunchtime), Theater, Video Animation, Video Production, Visual Art, Voice, Volleyball, Young Entrepreneurs
5th rowAfter-school Jazz Band, Annual Coffee House Concert, Annual Gallery Walk Art Exhibitions, Badminton, Baseball, Basketball, Borough Advisory Student Council, Boys Soccer, Community Service Learning, Competitive Ballroom Dancing, Creative Writing, Debate Committee, Debate Team, Educational Field Trips, Girls Volleyball, Green Club, Gay-Straight Alliance (GSA), Handball, Heart to Heart Charity, Kangaroo International Competition, Mandarin, Math Team, Model UN, National and Local Chess Championships, National Honor Society, NESTFest (Annual Talent Show), New York Math League Competition, Peer Leaders, Red Cross, Robotics, Scholastic Arts Competition, School Leadership Team (SLT), Social Justice, Softball, Student Government, The City Tones (Chorus), The Gauss Contest, The Purple Meet, Time Warner Cable, Ultimate Frisbee, Varsity Dance Team, Winter and Spring School Plays, World Science Festival, X-Country
ValueCountFrequency (%)
club 541
 
2.9%
student 480
 
2.6%
and 431
 
2.3%
team 316
 
1.7%
dance 287
 
1.6%
society 252
 
1.4%
government 249
 
1.4%
peer 226
 
1.2%
tutoring 219
 
1.2%
art 216
 
1.2%
Other values (2552) 15208
82.5%
2023-12-09T22:21:19.384930image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18007
 
12.4%
e 12058
 
8.3%
o 8665
 
6.0%
a 8604
 
5.9%
n 8311
 
5.7%
r 8277
 
5.7%
t 8252
 
5.7%
i 7945
 
5.5%
, 7463
 
5.1%
s 5198
 
3.6%
Other values (68) 52366
36.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 99618
68.6%
Uppercase Letter 18313
 
12.6%
Space Separator 18007
 
12.4%
Other Punctuation 8162
 
5.6%
Dash Punctuation 368
 
0.3%
Close Punctuation 295
 
0.2%
Open Punctuation 295
 
0.2%
Decimal Number 81
 
0.1%
Initial Punctuation 3
 
< 0.1%
Final Punctuation 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 12058
12.1%
o 8665
 
8.7%
a 8604
 
8.6%
n 8311
 
8.3%
r 8277
 
8.3%
t 8252
 
8.3%
i 7945
 
8.0%
s 5198
 
5.2%
l 4719
 
4.7%
u 4042
 
4.1%
Other values (16) 23547
23.6%
Uppercase Letter
ValueCountFrequency (%)
S 2629
14.4%
C 2382
13.0%
A 1554
 
8.5%
T 1356
 
7.4%
P 1349
 
7.4%
M 1169
 
6.4%
D 970
 
5.3%
G 750
 
4.1%
N 640
 
3.5%
H 634
 
3.5%
Other values (16) 4880
26.6%
Decimal Number
ValueCountFrequency (%)
2 21
25.9%
0 21
25.9%
3 11
13.6%
1 11
13.6%
5 5
 
6.2%
9 4
 
4.9%
8 3
 
3.7%
4 3
 
3.7%
6 1
 
1.2%
7 1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
, 7463
91.4%
/ 171
 
2.1%
. 143
 
1.8%
' 109
 
1.3%
; 102
 
1.2%
& 70
 
0.9%
" 57
 
0.7%
: 41
 
0.5%
! 6
 
0.1%
Space Separator
ValueCountFrequency (%)
18007
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 368
100.0%
Close Punctuation
ValueCountFrequency (%)
) 295
100.0%
Open Punctuation
ValueCountFrequency (%)
( 295
100.0%
Initial Punctuation
ValueCountFrequency (%)
3
100.0%
Final Punctuation
ValueCountFrequency (%)
3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 117931
81.2%
Common 27215
 
18.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 12058
 
10.2%
o 8665
 
7.3%
a 8604
 
7.3%
n 8311
 
7.0%
r 8277
 
7.0%
t 8252
 
7.0%
i 7945
 
6.7%
s 5198
 
4.4%
l 4719
 
4.0%
u 4042
 
3.4%
Other values (42) 41860
35.5%
Common
ValueCountFrequency (%)
18007
66.2%
, 7463
27.4%
- 368
 
1.4%
) 295
 
1.1%
( 295
 
1.1%
/ 171
 
0.6%
. 143
 
0.5%
' 109
 
0.4%
; 102
 
0.4%
& 70
 
0.3%
Other values (16) 192
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 145140
> 99.9%
Punctuation 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18007
 
12.4%
e 12058
 
8.3%
o 8665
 
6.0%
a 8604
 
5.9%
n 8311
 
5.7%
r 8277
 
5.7%
t 8252
 
5.7%
i 7945
 
5.5%
, 7463
 
5.1%
s 5198
 
3.6%
Other values (66) 52360
36.1%
Punctuation
ValueCountFrequency (%)
3
50.0%
3
50.0%

psal_sports_boys
Text

MISSING 

Distinct244
Distinct (%)69.9%
Missing73
Missing (%)17.3%
Memory size51.9 KiB
2023-12-09T22:21:19.609263image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length237
Median length153
Mean length88.14040115
Min length10

Characters and Unicode

Total characters30761
Distinct characters38
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique197 ?
Unique (%)56.4%

Sample

1st rowBasketball
2nd rowBaseball, Basketball, Bowling, Cross Country, Handball
3rd rowBaseball, Basketball, Soccer
4th rowBasketball, Rugby
5th rowBasketball, Fencing, Indoor Track
ValueCountFrequency (%)
basketball 533
13.4%
jv 412
10.4%
398
10.0%
baseball 384
9.7%
track 321
 
8.1%
soccer 226
 
5.7%
football 225
 
5.7%
volleyball 215
 
5.4%
outdoor 180
 
4.5%
bowling 143
 
3.6%
Other values (17) 942
23.7%
2023-12-09T22:21:19.992000image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 3708
 
12.1%
3630
 
11.8%
a 2892
 
9.4%
o 2035
 
6.6%
, 1972
 
6.4%
e 1628
 
5.3%
b 1497
 
4.9%
s 1450
 
4.7%
r 1268
 
4.1%
t 1206
 
3.9%
Other values (28) 9475
30.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 20768
67.5%
Uppercase Letter 3993
 
13.0%
Space Separator 3630
 
11.8%
Other Punctuation 2370
 
7.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 3708
17.9%
a 2892
13.9%
o 2035
9.8%
e 1628
7.8%
b 1497
7.2%
s 1450
 
7.0%
r 1268
 
6.1%
t 1206
 
5.8%
n 952
 
4.6%
k 876
 
4.2%
Other values (10) 3256
15.7%
Uppercase Letter
ValueCountFrequency (%)
B 1060
26.5%
V 627
15.7%
T 423
 
10.6%
J 412
 
10.3%
S 307
 
7.7%
C 277
 
6.9%
F 247
 
6.2%
O 180
 
4.5%
I 141
 
3.5%
H 122
 
3.1%
Other values (5) 197
 
4.9%
Other Punctuation
ValueCountFrequency (%)
, 1972
83.2%
& 398
 
16.8%
Space Separator
ValueCountFrequency (%)
3630
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 24761
80.5%
Common 6000
 
19.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 3708
15.0%
a 2892
11.7%
o 2035
 
8.2%
e 1628
 
6.6%
b 1497
 
6.0%
s 1450
 
5.9%
r 1268
 
5.1%
t 1206
 
4.9%
B 1060
 
4.3%
n 952
 
3.8%
Other values (25) 7065
28.5%
Common
ValueCountFrequency (%)
3630
60.5%
, 1972
32.9%
& 398
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30761
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 3708
 
12.1%
3630
 
11.8%
a 2892
 
9.4%
o 2035
 
6.6%
, 1972
 
6.4%
e 1628
 
5.3%
b 1497
 
4.9%
s 1450
 
4.7%
r 1268
 
4.1%
t 1206
 
3.9%
Other values (28) 9475
30.8%

psal_sports_girls
Text

MISSING 

Distinct233
Distinct (%)66.4%
Missing71
Missing (%)16.8%
Memory size45.4 KiB
2023-12-09T22:21:20.216673image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length225
Median length140
Mean length68.70940171
Min length5

Characters and Unicode

Total characters24117
Distinct characters38
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique181 ?
Unique (%)51.6%

Sample

1st rowSoftball
2nd rowBasketball, Bowling, Cross Country, Softball, Tennis
3rd rowBasketball, Soccer, Softball
4th rowRugby, Volleyball
5th rowBasketball, Fencing, Indoor Track
ValueCountFrequency (%)
basketball 385
13.2%
volleyball 323
11.1%
track 316
10.8%
softball 285
9.8%
outdoor 171
 
5.9%
jv 164
 
5.6%
soccer 163
 
5.6%
157
 
5.4%
indoor 145
 
5.0%
tennis 143
 
4.9%
Other values (16) 670
22.9%
2023-12-09T22:21:20.629606image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 2985
 
12.4%
2571
 
10.7%
a 1911
 
7.9%
o 1866
 
7.7%
, 1638
 
6.8%
r 1102
 
4.6%
e 1099
 
4.6%
b 1098
 
4.6%
t 1042
 
4.3%
s 916
 
3.8%
Other values (28) 7889
32.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 16822
69.8%
Uppercase Letter 2929
 
12.1%
Space Separator 2571
 
10.7%
Other Punctuation 1795
 
7.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 2985
17.7%
a 1911
11.4%
o 1866
11.1%
r 1102
 
6.6%
e 1099
 
6.5%
b 1098
 
6.5%
t 1042
 
6.2%
s 916
 
5.4%
n 889
 
5.3%
c 726
 
4.3%
Other values (10) 3188
19.0%
Uppercase Letter
ValueCountFrequency (%)
B 511
17.4%
S 502
17.1%
V 487
16.6%
T 459
15.7%
C 267
9.1%
O 171
 
5.8%
J 164
 
5.6%
I 145
 
5.0%
H 68
 
2.3%
G 58
 
2.0%
Other values (5) 97
 
3.3%
Other Punctuation
ValueCountFrequency (%)
, 1638
91.3%
& 157
 
8.7%
Space Separator
ValueCountFrequency (%)
2571
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 19751
81.9%
Common 4366
 
18.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 2985
15.1%
a 1911
 
9.7%
o 1866
 
9.4%
r 1102
 
5.6%
e 1099
 
5.6%
b 1098
 
5.6%
t 1042
 
5.3%
s 916
 
4.6%
n 889
 
4.5%
c 726
 
3.7%
Other values (25) 6117
31.0%
Common
ValueCountFrequency (%)
2571
58.9%
, 1638
37.5%
& 157
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24117
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 2985
 
12.4%
2571
 
10.7%
a 1911
 
7.9%
o 1866
 
7.7%
, 1638
 
6.8%
r 1102
 
4.6%
e 1099
 
4.6%
b 1098
 
4.6%
t 1042
 
4.3%
s 916
 
3.8%
Other values (28) 7889
32.7%

psal_sports_co_ed
Text

MISSING 

Distinct59
Distinct (%)44.7%
Missing290
Missing (%)68.7%
Memory size18.7 KiB
2023-12-09T22:21:20.849701image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length160
Median length42
Mean length16.96969697
Min length4

Characters and Unicode

Total characters2240
Distinct characters37
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)29.5%

Sample

1st rowSoccer
2nd rowRugby
3rd rowOutdoor Track
4th rowBowling, Tennis
5th rowBowling, Handball
ValueCountFrequency (%)
bowling 43
14.4%
track 27
 
9.1%
wrestling 24
 
8.1%
cricket 20
 
6.7%
outdoor 19
 
6.4%
handball 18
 
6.0%
cross 17
 
5.7%
country 17
 
5.7%
fencing 15
 
5.0%
tennis 15
 
5.0%
Other values (16) 83
27.9%
2023-12-09T22:21:21.245578image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 183
 
8.2%
o 168
 
7.5%
166
 
7.4%
l 165
 
7.4%
i 142
 
6.3%
r 137
 
6.1%
e 101
 
4.5%
, 101
 
4.5%
t 98
 
4.4%
g 96
 
4.3%
Other values (27) 883
39.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1671
74.6%
Uppercase Letter 298
 
13.3%
Space Separator 166
 
7.4%
Other Punctuation 105
 
4.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 183
11.0%
o 168
10.1%
l 165
9.9%
i 142
 
8.5%
r 137
 
8.2%
e 101
 
6.0%
t 98
 
5.9%
g 96
 
5.7%
a 89
 
5.3%
c 83
 
5.0%
Other values (10) 409
24.5%
Uppercase Letter
ValueCountFrequency (%)
C 54
18.1%
B 51
17.1%
T 42
14.1%
W 24
8.1%
S 20
 
6.7%
H 19
 
6.4%
O 19
 
6.4%
D 18
 
6.0%
F 17
 
5.7%
G 12
 
4.0%
Other values (4) 22
7.4%
Other Punctuation
ValueCountFrequency (%)
, 101
96.2%
& 4
 
3.8%
Space Separator
ValueCountFrequency (%)
166
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1969
87.9%
Common 271
 
12.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 183
 
9.3%
o 168
 
8.5%
l 165
 
8.4%
i 142
 
7.2%
r 137
 
7.0%
e 101
 
5.1%
t 98
 
5.0%
g 96
 
4.9%
a 89
 
4.5%
c 83
 
4.2%
Other values (24) 707
35.9%
Common
ValueCountFrequency (%)
166
61.3%
, 101
37.3%
& 4
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2240
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 183
 
8.2%
o 168
 
7.5%
166
 
7.4%
l 165
 
7.4%
i 142
 
6.3%
r 137
 
6.1%
e 101
 
4.5%
, 101
 
4.5%
t 98
 
4.4%
g 96
 
4.3%
Other values (27) 883
39.4%

school_sports
Text

MISSING 

Distinct281
Distinct (%)94.0%
Missing123
Missing (%)29.1%
Memory size41.1 KiB
2023-12-09T22:21:21.601185image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length372
Median length126
Mean length69.73578595
Min length6

Characters and Unicode

Total characters20851
Distinct characters74
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique274 ?
Unique (%)91.6%

Sample

1st rowBoxing, CHAMPS, Double Dutch, Table tennis, Track and Field
2nd rowInterscholastic Athletics, Fitness Center
3rd rowBasketball, Bicycling, Fitness, Flag Football, Indoor Soccer, Running, Skateboarding, Softball, Volleyball
4th rowHip-Hop, Volleyball, Zumba
5th rowBadminton, Baseball, Cross-Country, Dance, Outdoor Track, Soccer, Softball, Table Tennis, Volleyball
ValueCountFrequency (%)
basketball 144
 
5.2%
soccer 94
 
3.4%
volleyball 81
 
2.9%
sports 77
 
2.8%
intramural 66
 
2.4%
and 66
 
2.4%
football 63
 
2.3%
baseball 56
 
2.0%
cheerleading 56
 
2.0%
the 54
 
1.9%
Other values (428) 2016
72.7%
2023-12-09T22:21:22.139450image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2474
 
11.9%
l 1688
 
8.1%
a 1673
 
8.0%
e 1563
 
7.5%
o 1184
 
5.7%
t 1167
 
5.6%
s 962
 
4.6%
r 954
 
4.6%
n 940
 
4.5%
i 895
 
4.3%
Other values (64) 7351
35.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 15195
72.9%
Space Separator 2474
 
11.9%
Uppercase Letter 2137
 
10.2%
Other Punctuation 905
 
4.3%
Dash Punctuation 56
 
0.3%
Decimal Number 34
 
0.2%
Open Punctuation 24
 
0.1%
Close Punctuation 24
 
0.1%
Initial Punctuation 1
 
< 0.1%
Final Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 1688
11.1%
a 1673
11.0%
e 1563
10.3%
o 1184
 
7.8%
t 1167
 
7.7%
s 962
 
6.3%
r 954
 
6.3%
n 940
 
6.2%
i 895
 
5.9%
c 577
 
3.8%
Other values (16) 3592
23.6%
Uppercase Letter
ValueCountFrequency (%)
S 350
16.4%
B 281
13.1%
C 217
10.2%
F 192
9.0%
T 164
 
7.7%
A 122
 
5.7%
P 99
 
4.6%
V 97
 
4.5%
L 87
 
4.1%
I 80
 
3.7%
Other values (15) 448
21.0%
Other Punctuation
ValueCountFrequency (%)
, 722
79.8%
. 69
 
7.6%
; 47
 
5.2%
: 40
 
4.4%
& 13
 
1.4%
/ 7
 
0.8%
! 3
 
0.3%
' 2
 
0.2%
" 2
 
0.2%
Decimal Number
ValueCountFrequency (%)
2 8
23.5%
1 7
20.6%
0 5
14.7%
3 5
14.7%
7 3
 
8.8%
9 3
 
8.8%
8 2
 
5.9%
5 1
 
2.9%
Space Separator
ValueCountFrequency (%)
2474
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 17332
83.1%
Common 3519
 
16.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 1688
 
9.7%
a 1673
 
9.7%
e 1563
 
9.0%
o 1184
 
6.8%
t 1167
 
6.7%
s 962
 
5.6%
r 954
 
5.5%
n 940
 
5.4%
i 895
 
5.2%
c 577
 
3.3%
Other values (41) 5729
33.1%
Common
ValueCountFrequency (%)
2474
70.3%
, 722
 
20.5%
. 69
 
2.0%
- 56
 
1.6%
; 47
 
1.3%
: 40
 
1.1%
( 24
 
0.7%
) 24
 
0.7%
& 13
 
0.4%
2 8
 
0.2%
Other values (13) 42
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20849
> 99.9%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2474
 
11.9%
l 1688
 
8.1%
a 1673
 
8.0%
e 1563
 
7.5%
o 1184
 
5.7%
t 1167
 
5.6%
s 962
 
4.6%
r 954
 
4.6%
n 940
 
4.5%
i 895
 
4.3%
Other values (62) 7349
35.2%
Punctuation
ValueCountFrequency (%)
1
50.0%
1
50.0%

import_info_drop_down
Text

MISSING 

Distinct72
Distinct (%)32.6%
Missing201
Missing (%)47.6%
Memory size32.7 KiB
2023-12-09T22:21:22.372133image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length186
Median length129
Mean length64.67873303
Min length19

Characters and Unicode

Total characters14294
Distinct characters35
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)17.2%

Sample

1st rowExtended Day Program, Internship Requirement, Weekend Program offered
2nd rowOur school requires an Academic Portfolio for graduation
3rd rowCommunity Service Requirement, Extended Day Program, Student Summer Orientation, Summer Internship Program offered, Weekend Program offered
4th rowStudent Summer Orientation
5th rowCommunity Service Requirement, Extended Day Program, Student Summer Orientation, Weekend Program offered
ValueCountFrequency (%)
program 228
13.7%
requirement 180
10.8%
extended 128
 
7.7%
day 128
 
7.7%
summer 121
 
7.2%
community 115
 
6.9%
service 115
 
6.9%
student 102
 
6.1%
orientation 102
 
6.1%
offered 100
 
6.0%
Other values (15) 351
21.0%
2023-12-09T22:21:22.782522image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1960
13.7%
1449
 
10.1%
r 1294
 
9.1%
n 979
 
6.8%
t 936
 
6.5%
m 908
 
6.4%
i 783
 
5.5%
o 713
 
5.0%
d 603
 
4.2%
u 598
 
4.2%
Other values (25) 4071
28.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11085
77.6%
Uppercase Letter 1460
 
10.2%
Space Separator 1449
 
10.1%
Other Punctuation 300
 
2.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1960
17.7%
r 1294
11.7%
n 979
8.8%
t 936
8.4%
m 908
8.2%
i 783
 
7.1%
o 713
 
6.4%
d 603
 
5.4%
u 598
 
5.4%
a 545
 
4.9%
Other values (12) 1766
15.9%
Uppercase Letter
ValueCountFrequency (%)
S 338
23.2%
P 250
17.1%
R 194
13.3%
D 135
 
9.2%
E 128
 
8.8%
O 124
 
8.5%
C 122
 
8.4%
W 81
 
5.5%
I 59
 
4.0%
A 22
 
1.5%
Space Separator
ValueCountFrequency (%)
1449
100.0%
Other Punctuation
ValueCountFrequency (%)
, 300
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12545
87.8%
Common 1749
 
12.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1960
15.6%
r 1294
10.3%
n 979
 
7.8%
t 936
 
7.5%
m 908
 
7.2%
i 783
 
6.2%
o 713
 
5.7%
d 603
 
4.8%
u 598
 
4.8%
a 545
 
4.3%
Other values (23) 3226
25.7%
Common
ValueCountFrequency (%)
1449
82.8%
, 300
 
17.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14294
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1960
13.7%
1449
 
10.1%
r 1294
 
9.1%
n 979
 
6.8%
t 936
 
6.5%
m 908
 
6.4%
i 783
 
5.5%
o 713
 
5.0%
d 603
 
4.2%
u 598
 
4.2%
Other values (25) 4071
28.5%

import_info_free_text
Text

MISSING 

Distinct333
Distinct (%)98.5%
Missing84
Missing (%)19.9%
Memory size101.3 KiB
2023-12-09T22:21:23.584442image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1132
Median length306.5
Mean length231.0502959
Min length12

Characters and Unicode

Total characters78095
Distinct characters80
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique328 ?
Unique (%)97.0%

Sample

1st rowStudents are encouraged to wear a shirt with the University Neighborhood High School (UNHS) logo, Incoming students are expected to attend School Orientation in June, Community Service required (60 hours)
2nd rowEast Side Community School is a member of the New York Performance Standards Consortium. For more information, visit www.performanceassessment.org., Students present and defend their work to committees twice a year through our portfolio roundtable presentations. Students also must complete Performance-based Assessment Tasks (PBATs) such as a college-level history research paper and a student-designed science experiment as a replacement for the math, science and history Regents Exams.
3rd rowRequirements include 60 hours of Community Service that may be fulfilled through internships, service to the MVHS community or through independent projects that students design and develop, Summer Bridge to Success Program for incoming students in July, Students Dress for Success in "Smart Casual" attire, Model Peer Leadership Program, Opportunity to Graduate Early, Innovative Advisory Program, State-of-the-art Earth Science, Living Environment and Chemistry Science Labs under construction, Mastery-based Grading System, Model Blended Online Instructional Program
4th row9th grade math and science are single gender classes., Interested candidates for 9th and 10th grade must take our school-based qualifying exam. See our website www.nestmk12.net for exam dates and to register., Dress Code Required: Business Casual - shirt/blouse, khaki, corduroy or dark denim (navy, black, brown, dark gray) pants, dress slacks/skirt/dress. On Assembly Days, students wear job interview clothing (Boys - shirt and tie, optional blazer)., Community Service Requirement - All Upper School students are required to complete 60 hours of Community Service.
5th rowStudents may apply to both schools. They must, however, indicate each one as a separate choice on the Department of Education High School Application., Students only need to take one assessment in order to apply to either or both schools. The assessment may be taken at either our Manhattan or Queens location., Students who demonstrate strong abilities in their grades and the assessment will be invited to an interview at BHSEC. Students receive an email invitation for an interview., When evaluating applicants, BHSEC seeks to build an incoming 9th grade class that is representative of the entire City of New York., To be considered for admission to Bard High School Early College (and/or Queens Campus), student report cards should reflect a cumulative average of an 85 or above in English, Math, Science, and Social Studies., All students wishing to be considered for admission to Bard High School Early College (and/or Queens Campus) must register online via the school's website at www.bard.edu/bhsec. Registration for the assessment begins September 3, 2013.
ValueCountFrequency (%)
required 318
 
2.8%
school 285
 
2.5%
and 285
 
2.5%
for 220
 
2.0%
or 219
 
1.9%
the 215
 
1.9%
black 207
 
1.8%
students 189
 
1.7%
to 185
 
1.6%
shirt 159
 
1.4%
Other values (1628) 8974
79.7%
2023-12-09T22:21:24.189964image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11007
14.1%
e 7029
 
9.0%
r 5144
 
6.6%
o 5042
 
6.5%
t 4665
 
6.0%
s 4515
 
5.8%
a 4425
 
5.7%
i 4220
 
5.4%
n 3914
 
5.0%
l 2671
 
3.4%
Other values (70) 25463
32.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 60047
76.9%
Space Separator 11007
 
14.1%
Uppercase Letter 3623
 
4.6%
Other Punctuation 2277
 
2.9%
Decimal Number 522
 
0.7%
Dash Punctuation 311
 
0.4%
Close Punctuation 145
 
0.2%
Open Punctuation 145
 
0.2%
Final Punctuation 8
 
< 0.1%
Initial Punctuation 8
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 7029
11.7%
r 5144
 
8.6%
o 5042
 
8.4%
t 4665
 
7.8%
s 4515
 
7.5%
a 4425
 
7.4%
i 4220
 
7.0%
n 3914
 
6.5%
l 2671
 
4.4%
d 2635
 
4.4%
Other values (16) 15787
26.3%
Uppercase Letter
ValueCountFrequency (%)
S 560
15.5%
P 351
9.7%
A 348
9.6%
R 327
 
9.0%
C 318
 
8.8%
D 217
 
6.0%
E 211
 
5.8%
O 162
 
4.5%
T 157
 
4.3%
U 149
 
4.1%
Other values (14) 823
22.7%
Other Punctuation
ValueCountFrequency (%)
, 1234
54.2%
/ 328
 
14.4%
. 287
 
12.6%
: 281
 
12.3%
; 77
 
3.4%
' 32
 
1.4%
" 14
 
0.6%
& 13
 
0.6%
* 7
 
0.3%
@ 2
 
0.1%
Other values (2) 2
 
0.1%
Decimal Number
ValueCountFrequency (%)
0 120
23.0%
1 117
22.4%
2 76
14.6%
3 53
10.2%
9 46
 
8.8%
5 36
 
6.9%
4 30
 
5.7%
8 26
 
5.0%
6 12
 
2.3%
7 6
 
1.1%
Space Separator
ValueCountFrequency (%)
11007
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 311
100.0%
Close Punctuation
ValueCountFrequency (%)
) 145
100.0%
Open Punctuation
ValueCountFrequency (%)
( 145
100.0%
Final Punctuation
ValueCountFrequency (%)
8
100.0%
Initial Punctuation
ValueCountFrequency (%)
8
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 63670
81.5%
Common 14425
 
18.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 7029
 
11.0%
r 5144
 
8.1%
o 5042
 
7.9%
t 4665
 
7.3%
s 4515
 
7.1%
a 4425
 
6.9%
i 4220
 
6.6%
n 3914
 
6.1%
l 2671
 
4.2%
d 2635
 
4.1%
Other values (40) 19410
30.5%
Common
ValueCountFrequency (%)
11007
76.3%
, 1234
 
8.6%
/ 328
 
2.3%
- 311
 
2.2%
. 287
 
2.0%
: 281
 
1.9%
) 145
 
1.0%
( 145
 
1.0%
0 120
 
0.8%
1 117
 
0.8%
Other values (20) 450
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78079
> 99.9%
Punctuation 16
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11007
14.1%
e 7029
 
9.0%
r 5144
 
6.6%
o 5042
 
6.5%
t 4665
 
6.0%
s 4515
 
5.8%
a 4425
 
5.7%
i 4220
 
5.4%
n 3914
 
5.0%
l 2671
 
3.4%
Other values (68) 25447
32.6%
Punctuation
ValueCountFrequency (%)
8
50.0%
8
50.0%
Distinct33
Distinct (%)7.9%
Missing3
Missing (%)0.7%
Memory size26.4 KiB
2023-12-09T22:21:24.388779image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length7
Mean length7.002386635
Min length7

Characters and Unicode

Total characters2934
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)4.1%

Sample

1st row8:30 AM
2nd row8:15 AM
3rd row8:30 AM
4th row8:15 AM
5th row8:15 AM
ValueCountFrequency (%)
am 419
50.0%
8:00 158
 
18.9%
8:30 76
 
9.1%
8:15 61
 
7.3%
8:45 34
 
4.1%
9:00 26
 
3.1%
7:45 8
 
1.0%
8:40 6
 
0.7%
8:25 5
 
0.6%
8:20 5
 
0.6%
Other values (24) 40
 
4.8%
2023-12-09T22:21:24.686114image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 476
16.2%
: 419
14.3%
419
14.3%
A 419
14.3%
M 419
14.3%
8 365
12.4%
5 131
 
4.5%
3 87
 
3.0%
1 77
 
2.6%
4 50
 
1.7%
Other values (4) 72
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1258
42.9%
Uppercase Letter 838
28.6%
Other Punctuation 419
 
14.3%
Space Separator 419
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 476
37.8%
8 365
29.0%
5 131
 
10.4%
3 87
 
6.9%
1 77
 
6.1%
4 50
 
4.0%
9 33
 
2.6%
7 23
 
1.8%
2 15
 
1.2%
6 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
A 419
50.0%
M 419
50.0%
Other Punctuation
ValueCountFrequency (%)
: 419
100.0%
Space Separator
ValueCountFrequency (%)
419
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2096
71.4%
Latin 838
 
28.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 476
22.7%
: 419
20.0%
419
20.0%
8 365
17.4%
5 131
 
6.2%
3 87
 
4.2%
1 77
 
3.7%
4 50
 
2.4%
9 33
 
1.6%
7 23
 
1.1%
Other values (2) 16
 
0.8%
Latin
ValueCountFrequency (%)
A 419
50.0%
M 419
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2934
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 476
16.2%
: 419
14.3%
419
14.3%
A 419
14.3%
M 419
14.3%
8 365
12.4%
5 131
 
4.5%
3 87
 
3.0%
1 77
 
2.6%
4 50
 
1.7%
Other values (4) 72
 
2.5%
Distinct42
Distinct (%)10.0%
Missing3
Missing (%)0.7%
Memory size26.4 KiB
2023-12-09T22:21:24.885189image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters2933
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)4.1%

Sample

1st row3:30 PM
2nd row3:15 PM
3rd row3:30 PM
4th row3:30 PM
5th row4:00 PM
ValueCountFrequency (%)
pm 418
49.9%
3:00 87
 
10.4%
3:30 67
 
8.0%
3:15 55
 
6.6%
3:45 43
 
5.1%
4:00 33
 
3.9%
2:45 30
 
3.6%
2:30 14
 
1.7%
3:20 9
 
1.1%
4:15 7
 
0.8%
Other values (33) 75
 
8.9%
2023-12-09T22:21:25.196449image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 419
14.3%
419
14.3%
M 419
14.3%
P 418
14.3%
3 384
13.1%
0 383
13.1%
5 172
5.9%
4 136
 
4.6%
2 92
 
3.1%
1 77
 
2.6%
Other values (5) 14
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1257
42.9%
Uppercase Letter 838
28.6%
Other Punctuation 419
 
14.3%
Space Separator 419
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 384
30.5%
0 383
30.5%
5 172
13.7%
4 136
 
10.8%
2 92
 
7.3%
1 77
 
6.1%
7 8
 
0.6%
9 3
 
0.2%
6 1
 
0.1%
8 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
M 419
50.0%
P 418
49.9%
A 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
: 419
100.0%
Space Separator
ValueCountFrequency (%)
419
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2095
71.4%
Latin 838
 
28.6%

Most frequent character per script

Common
ValueCountFrequency (%)
: 419
20.0%
419
20.0%
3 384
18.3%
0 383
18.3%
5 172
8.2%
4 136
 
6.5%
2 92
 
4.4%
1 77
 
3.7%
7 8
 
0.4%
9 3
 
0.1%
Other values (2) 2
 
0.1%
Latin
ValueCountFrequency (%)
M 419
50.0%
P 418
49.9%
A 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2933
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 419
14.3%
419
14.3%
M 419
14.3%
P 418
14.3%
3 384
13.1%
0 383
13.1%
5 172
5.9%
4 136
 
4.6%
2 92
 
3.1%
1 77
 
2.6%
Other values (5) 14
 
0.5%
Distinct300
Distinct (%)71.3%
Missing1
Missing (%)0.2%
Memory size73.1 KiB
2023-12-09T22:21:25.592582image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1025
Median length300
Mean length120.4085511
Min length45

Characters and Unicode

Total characters50692
Distinct characters77
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique293 ?
Unique (%)69.6%

Sample

1st rowWe cordially invite you to a guided tour of our school every Wednesday between the hours of 10-11 am. Please call us at 212-406-9411 x446 if you prefer a private appointment.
2nd rowPlease call Lisa Ranson, our parent coordinator, at 212-962-4341 ext. 2121 for Open House information.
3rd rowSee our website (www.eschs.org) for Open House information.
4th rowWe host Open Houses throughout the year. Please call or email Alicia Carlson (212-473-8152 or acarlson@schools.nyc.gov) for an appointment. We love visitors!
5th rowFor Open House dates and admissions information, please check our website, www.nestmk12.net.
ValueCountFrequency (%)
for 404
 
4.9%
open 398
 
4.9%
please 355
 
4.3%
the 352
 
4.3%
school 321
 
3.9%
house 316
 
3.9%
and 307
 
3.7%
our 265
 
3.2%
information 191
 
2.3%
contact 185
 
2.3%
Other values (975) 5093
62.2%
2023-12-09T22:21:26.173041image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7766
15.3%
e 4628
 
9.1%
o 3988
 
7.9%
a 3004
 
5.9%
t 2981
 
5.9%
s 2682
 
5.3%
n 2593
 
5.1%
r 2444
 
4.8%
i 2009
 
4.0%
l 1878
 
3.7%
Other values (67) 16719
33.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 36278
71.6%
Space Separator 7766
 
15.3%
Decimal Number 2424
 
4.8%
Uppercase Letter 2380
 
4.7%
Other Punctuation 1498
 
3.0%
Dash Punctuation 297
 
0.6%
Open Punctuation 25
 
< 0.1%
Close Punctuation 24
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4628
12.8%
o 3988
11.0%
a 3004
 
8.3%
t 2981
 
8.2%
s 2682
 
7.4%
n 2593
 
7.1%
r 2444
 
6.7%
i 2009
 
5.5%
l 1878
 
5.2%
c 1533
 
4.2%
Other values (16) 8538
23.5%
Uppercase Letter
ValueCountFrequency (%)
O 589
24.7%
P 450
18.9%
H 416
17.5%
M 193
 
8.1%
N 111
 
4.7%
S 108
 
4.5%
T 98
 
4.1%
A 67
 
2.8%
F 64
 
2.7%
W 54
 
2.3%
Other values (16) 230
 
9.7%
Other Punctuation
ValueCountFrequency (%)
. 843
56.3%
, 371
24.8%
: 171
 
11.4%
@ 30
 
2.0%
; 29
 
1.9%
/ 28
 
1.9%
' 8
 
0.5%
& 7
 
0.5%
! 7
 
0.5%
? 2
 
0.1%
Decimal Number
ValueCountFrequency (%)
0 506
20.9%
1 435
17.9%
2 348
14.4%
3 277
11.4%
7 195
 
8.0%
8 180
 
7.4%
6 151
 
6.2%
5 126
 
5.2%
4 109
 
4.5%
9 97
 
4.0%
Space Separator
ValueCountFrequency (%)
7766
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 297
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 38658
76.3%
Common 12034
 
23.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4628
12.0%
o 3988
 
10.3%
a 3004
 
7.8%
t 2981
 
7.7%
s 2682
 
6.9%
n 2593
 
6.7%
r 2444
 
6.3%
i 2009
 
5.2%
l 1878
 
4.9%
c 1533
 
4.0%
Other values (42) 10918
28.2%
Common
ValueCountFrequency (%)
7766
64.5%
. 843
 
7.0%
0 506
 
4.2%
1 435
 
3.6%
, 371
 
3.1%
2 348
 
2.9%
- 297
 
2.5%
3 277
 
2.3%
7 195
 
1.6%
8 180
 
1.5%
Other values (15) 816
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50692
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7766
15.3%
e 4628
 
9.1%
o 3988
 
7.9%
a 3004
 
5.9%
t 2981
 
5.9%
s 2682
 
5.3%
n 2593
 
5.1%
r 2444
 
4.8%
i 2009
 
4.0%
l 1878
 
3.7%
Other values (67) 16719
33.0%
Distinct2
Distinct (%)0.5%
Missing1
Missing (%)0.2%
Memory size65.5 KiB
2023-12-09T22:21:26.398934image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length102
Median length102
Mean length101.9643705
Min length101

Characters and Unicode

Total characters42927
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowThis school will provide students with disabilities the supports and services indicated on their IEPs.
2nd rowThis school will provide students with disabilities the supports and services indicated on their IEPs.
3rd rowThis school will provide students with disabilities the supports and services indicated on their IEPs.
4th rowThis school will provide students with disabilities the supports and services indicated on their IEPs.
5th rowThis school will provide students with disabilities the supports and services indicated on their IEPs.
ValueCountFrequency (%)
this 421
 
6.7%
school 421
 
6.7%
will 421
 
6.7%
provide 421
 
6.7%
students 421
 
6.7%
with 421
 
6.7%
disabilities 421
 
6.7%
the 421
 
6.7%
supports 421
 
6.7%
and 421
 
6.7%
Other values (5) 2105
33.3%
2023-12-09T22:21:26.723594image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5894
13.7%
i 5052
11.8%
s 4631
10.8%
e 3368
 
7.8%
t 3368
 
7.8%
d 2526
 
5.9%
o 2105
 
4.9%
h 2105
 
4.9%
l 1684
 
3.9%
n 1684
 
3.9%
Other values (13) 10510
24.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34943
81.4%
Space Separator 5894
 
13.7%
Uppercase Letter 1684
 
3.9%
Other Punctuation 406
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 5052
14.5%
s 4631
13.3%
e 3368
9.6%
t 3368
9.6%
d 2526
 
7.2%
o 2105
 
6.0%
h 2105
 
6.0%
l 1684
 
4.8%
n 1684
 
4.8%
r 1684
 
4.8%
Other values (7) 6736
19.3%
Uppercase Letter
ValueCountFrequency (%)
E 421
25.0%
P 421
25.0%
T 421
25.0%
I 421
25.0%
Space Separator
ValueCountFrequency (%)
5894
100.0%
Other Punctuation
ValueCountFrequency (%)
. 406
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 36627
85.3%
Common 6300
 
14.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 5052
13.8%
s 4631
12.6%
e 3368
 
9.2%
t 3368
 
9.2%
d 2526
 
6.9%
o 2105
 
5.7%
h 2105
 
5.7%
l 1684
 
4.6%
n 1684
 
4.6%
r 1684
 
4.6%
Other values (11) 8420
23.0%
Common
ValueCountFrequency (%)
5894
93.6%
. 406
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42927
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5894
13.7%
i 5052
11.8%
s 4631
10.8%
e 3368
 
7.8%
t 3368
 
7.8%
d 2526
 
5.9%
o 2105
 
4.9%
h 2105
 
4.9%
l 1684
 
3.9%
n 1684
 
3.9%
Other values (13) 10510
24.5%

online_ap_courses
Text

MISSING 

Distinct40
Distinct (%)87.0%
Missing376
Missing (%)89.1%
Memory size17.8 KiB
2023-12-09T22:21:26.970019image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length359
Median length76.5
Mean length75.08695652
Min length7

Characters and Unicode

Total characters3454
Distinct characters37
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)76.1%

Sample

1st rowChinese Language and Culture, Spanish Literature
2nd rowCalculus AB, English Language and Composition
3rd rowBiology, Chemistry, Chinese Language and Culture, English Language and Composition, United States History, World History
4th rowEnglish Language and Composition, Spanish Language
5th rowChemistry
ValueCountFrequency (%)
history 36
 
8.5%
and 35
 
8.2%
language 28
 
6.6%
english 24
 
5.6%
composition 24
 
5.6%
united 22
 
5.2%
states 22
 
5.2%
literature 20
 
4.7%
biology 19
 
4.5%
calculus 16
 
3.8%
Other values (32) 179
42.1%
2023-12-09T22:21:27.390971image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
379
 
11.0%
i 273
 
7.9%
o 243
 
7.0%
t 232
 
6.7%
n 225
 
6.5%
s 199
 
5.8%
e 197
 
5.7%
a 192
 
5.6%
r 159
 
4.6%
, 138
 
4.0%
Other values (27) 1217
35.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2507
72.6%
Uppercase Letter 407
 
11.8%
Space Separator 379
 
11.0%
Other Punctuation 161
 
4.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 273
10.9%
o 243
9.7%
t 232
9.3%
n 225
 
9.0%
s 199
 
7.9%
e 197
 
7.9%
a 192
 
7.7%
r 159
 
6.3%
c 110
 
4.4%
l 109
 
4.3%
Other values (9) 568
22.7%
Uppercase Letter
ValueCountFrequency (%)
C 68
16.7%
L 50
12.3%
S 50
12.3%
E 48
11.8%
B 43
10.6%
H 38
9.3%
A 23
 
5.7%
U 22
 
5.4%
P 19
 
4.7%
M 15
 
3.7%
Other values (5) 31
7.6%
Other Punctuation
ValueCountFrequency (%)
, 138
85.7%
: 23
 
14.3%
Space Separator
ValueCountFrequency (%)
379
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2914
84.4%
Common 540
 
15.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 273
 
9.4%
o 243
 
8.3%
t 232
 
8.0%
n 225
 
7.7%
s 199
 
6.8%
e 197
 
6.8%
a 192
 
6.6%
r 159
 
5.5%
c 110
 
3.8%
l 109
 
3.7%
Other values (24) 975
33.5%
Common
ValueCountFrequency (%)
379
70.2%
, 138
 
25.6%
: 23
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3454
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
379
 
11.0%
i 273
 
7.9%
o 243
 
7.0%
t 232
 
6.7%
n 225
 
6.5%
s 199
 
5.8%
e 197
 
5.7%
a 192
 
5.6%
r 159
 
4.6%
, 138
 
4.0%
Other values (27) 1217
35.2%
Distinct32
Distinct (%)61.5%
Missing370
Missing (%)87.7%
Memory size16.1 KiB
2023-12-09T22:21:27.606899image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length169
Median length92.5
Mean length30.59615385
Min length6

Characters and Unicode

Total characters1591
Distinct characters42
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)55.8%

Sample

1st rowChinese (Mandarin), Spanish
2nd rowAmerican Sign Language, Arabic, Chinese (Mandarin), English, French, German, Hebrew, Italian, Japanese, Korean, Latin, Modern Greek, Polish, Portuguese, Russian, Spanish
3rd rowChinese (Mandarin), French, German, Spanish
4th rowFrench, Spanish
5th rowFrench, Spanish
ValueCountFrequency (%)
spanish 39
20.2%
french 26
13.5%
chinese 17
8.8%
german 14
 
7.3%
latin 12
 
6.2%
italian 11
 
5.7%
japanese 10
 
5.2%
english 8
 
4.1%
mandarin 8
 
4.1%
arabic 6
 
3.1%
Other values (17) 42
21.8%
2023-12-09T22:21:27.981739image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 177
11.1%
a 160
 
10.1%
141
 
8.9%
e 134
 
8.4%
, 122
 
7.7%
i 122
 
7.7%
s 99
 
6.2%
h 93
 
5.8%
r 78
 
4.9%
p 49
 
3.1%
Other values (32) 416
26.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1111
69.8%
Uppercase Letter 196
 
12.3%
Space Separator 141
 
8.9%
Other Punctuation 122
 
7.7%
Close Punctuation 9
 
0.6%
Open Punctuation 9
 
0.6%
Dash Punctuation 3
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 177
15.9%
a 160
14.4%
e 134
12.1%
i 122
11.0%
s 99
8.9%
h 93
8.4%
r 78
7.0%
p 49
 
4.4%
t 36
 
3.2%
c 34
 
3.1%
Other values (10) 129
11.6%
Uppercase Letter
ValueCountFrequency (%)
S 40
20.4%
F 26
13.3%
C 22
11.2%
G 16
 
8.2%
L 15
 
7.7%
I 11
 
5.6%
J 10
 
5.1%
M 9
 
4.6%
A 9
 
4.6%
E 8
 
4.1%
Other values (7) 30
15.3%
Space Separator
ValueCountFrequency (%)
141
100.0%
Other Punctuation
ValueCountFrequency (%)
, 122
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1307
82.1%
Common 284
 
17.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 177
13.5%
a 160
12.2%
e 134
10.3%
i 122
 
9.3%
s 99
 
7.6%
h 93
 
7.1%
r 78
 
6.0%
p 49
 
3.7%
S 40
 
3.1%
t 36
 
2.8%
Other values (27) 319
24.4%
Common
ValueCountFrequency (%)
141
49.6%
, 122
43.0%
) 9
 
3.2%
( 9
 
3.2%
- 3
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1591
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 177
11.1%
a 160
 
10.1%
141
 
8.9%
e 134
 
8.4%
, 122
 
7.7%
i 122
 
7.7%
s 99
 
6.2%
h 93
 
5.8%
r 78
 
4.9%
p 49
 
3.1%
Other values (32) 416
26.1%

header01
Text

MISSING 

Distinct14
Distinct (%)56.0%
Missing397
Missing (%)94.1%
Memory size15.5 KiB
2023-12-09T22:21:28.347606image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length358
Median length19
Mean length66.48
Min length19

Characters and Unicode

Total characters1662
Distinct characters61
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)48.0%

Sample

1st row2013 Audition Dates
2nd row2013 Audition Dates
3rd row2013 Audition Dates It is important to arrive on time and be prepared, as outlined in the audition guidelines. Students who arrive after 10:00 AM will NOT be auditioned. You may audition for a maximum of two possible arts majors on a given day, if time permits. For auditions, use the Julia Richman Educational Campus (JREC) entrance at 317 East 67th Street.
4th row2013 Audition Dates
5th rowAll students can audition for the High School of Fashion Industries in 1 of 2 ways: 1) Online: Submit an online audition by visiting the school website at www.fashionhighschool.net. 2) In Person: Audition in person on the dates listed below. No reservations are necessary.
ValueCountFrequency (%)
audition 30
 
11.0%
dates 25
 
9.2%
2013 23
 
8.5%
the 8
 
2.9%
in 6
 
2.2%
on 6
 
2.2%
arrive 5
 
1.8%
as 5
 
1.8%
be 5
 
1.8%
are 4
 
1.5%
Other values (108) 155
57.0%
2023-12-09T22:21:28.914028image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
247
14.9%
e 123
 
7.4%
i 122
 
7.3%
t 116
 
7.0%
o 105
 
6.3%
a 95
 
5.7%
n 93
 
5.6%
s 73
 
4.4%
d 59
 
3.5%
r 57
 
3.4%
Other values (51) 572
34.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1111
66.8%
Space Separator 247
 
14.9%
Decimal Number 146
 
8.8%
Uppercase Letter 118
 
7.1%
Other Punctuation 30
 
1.8%
Close Punctuation 4
 
0.2%
Dash Punctuation 4
 
0.2%
Open Punctuation 2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 123
11.1%
i 122
11.0%
t 116
10.4%
o 105
9.5%
a 95
8.6%
n 93
8.4%
s 73
 
6.6%
d 59
 
5.3%
r 57
 
5.1%
u 54
 
4.9%
Other values (14) 214
19.3%
Uppercase Letter
ValueCountFrequency (%)
A 30
25.4%
D 28
23.7%
I 9
 
7.6%
S 8
 
6.8%
N 6
 
5.1%
E 5
 
4.2%
O 5
 
4.2%
T 5
 
4.2%
P 4
 
3.4%
R 3
 
2.5%
Other values (10) 15
12.7%
Decimal Number
ValueCountFrequency (%)
1 36
24.7%
0 32
21.9%
2 32
21.9%
3 26
17.8%
6 5
 
3.4%
5 5
 
3.4%
4 4
 
2.7%
7 3
 
2.1%
8 2
 
1.4%
9 1
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 17
56.7%
, 8
26.7%
: 5
 
16.7%
Space Separator
ValueCountFrequency (%)
247
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1229
73.9%
Common 433
 
26.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 123
 
10.0%
i 122
 
9.9%
t 116
 
9.4%
o 105
 
8.5%
a 95
 
7.7%
n 93
 
7.6%
s 73
 
5.9%
d 59
 
4.8%
r 57
 
4.6%
u 54
 
4.4%
Other values (34) 332
27.0%
Common
ValueCountFrequency (%)
247
57.0%
1 36
 
8.3%
0 32
 
7.4%
2 32
 
7.4%
3 26
 
6.0%
. 17
 
3.9%
, 8
 
1.8%
6 5
 
1.2%
: 5
 
1.2%
5 5
 
1.2%
Other values (7) 20
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1662
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
247
14.9%
e 123
 
7.4%
i 122
 
7.3%
t 116
 
7.0%
o 105
 
6.3%
a 95
 
5.7%
n 93
 
5.6%
s 73
 
4.4%
d 59
 
3.5%
r 57
 
3.4%
Other values (51) 572
34.4%

footer01
Text

MISSING 

Distinct16
Distinct (%)64.0%
Missing397
Missing (%)94.1%
Memory size18.6 KiB
2023-12-09T22:21:29.331850image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length919
Median length588
Mean length192.36
Min length1

Characters and Unicode

Total characters4809
Distinct characters71
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)60.0%

Sample

1st row0
2nd rowDRAMA AND VOCAL AUDITIONS: Professional Performing Arts High School (PPAS), 328 West 48th Street, between 8th and 9th Avenues, Manhattan. DANCE AUDITIONS: The Ailey School at The Joan Weill Center for Dance, 405 West 55th Street at 9th Avenue, Manhattan. MUSICAL THEATRE AUDITIONS: Rosie's Theater Kids at the Maravel Arts Center, 445 West 45th Street, between 9th/10th Avenues, Manhattan. Please print and fill out an audition form from our website, www.ppasnyc.org, and bring it with you on the day of your audition. If you are unable to attend on your assigned date, your guidance counselor must contact PPAS to arrange an alternative date by emailing admissions@ppasshare.org or calling the Admissions Director at 212-247-8652. There are no auditions after December 8, 2013. The audition process may take up to 4 hours; it is advisable that parents drop students off and pick them up when the audition is completed.
3rd rowWhen there is a conflict, you may audition on a date other than your borough date.
4th rowPlease call the school to schedule an audition appointment.
5th rowPlease bring your portfolio if you are auditioning in person. The school will be offering portfolio workshops for applicants. Please check www.fashionhighschool.net for the specific dates and times of these workshops. If you have any questions please contact Ms. Silva (212-255-1235 ext. 2015 or dsilva3@schools.nyc.gov) or Ms. Chavez (212-255-1235 ext. 2016 or rchavez5@schools.nyc.gov).
ValueCountFrequency (%)
the 28
 
3.7%
to 26
 
3.4%
audition 19
 
2.5%
for 18
 
2.3%
and 16
 
2.1%
a 16
 
2.1%
you 14
 
1.8%
of 12
 
1.6%
on 11
 
1.4%
are 11
 
1.4%
Other values (318) 595
77.7%
2023-12-09T22:21:29.835102image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
741
15.4%
e 388
 
8.1%
o 357
 
7.4%
t 317
 
6.6%
a 306
 
6.4%
i 278
 
5.8%
n 259
 
5.4%
r 236
 
4.9%
s 220
 
4.6%
d 151
 
3.1%
Other values (61) 1556
32.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3558
74.0%
Space Separator 741
 
15.4%
Uppercase Letter 220
 
4.6%
Other Punctuation 142
 
3.0%
Decimal Number 114
 
2.4%
Dash Punctuation 18
 
0.4%
Open Punctuation 8
 
0.2%
Close Punctuation 8
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 388
10.9%
o 357
 
10.0%
t 317
 
8.9%
a 306
 
8.6%
i 278
 
7.8%
n 259
 
7.3%
r 236
 
6.6%
s 220
 
6.2%
d 151
 
4.2%
l 141
 
4.0%
Other values (16) 905
25.4%
Uppercase Letter
ValueCountFrequency (%)
A 36
16.4%
T 27
12.3%
S 26
11.8%
M 19
8.6%
P 18
 
8.2%
I 12
 
5.5%
N 11
 
5.0%
D 9
 
4.1%
L 8
 
3.6%
C 7
 
3.2%
Other values (14) 47
21.4%
Decimal Number
ValueCountFrequency (%)
0 23
20.2%
2 22
19.3%
5 18
15.8%
1 14
12.3%
4 9
 
7.9%
3 9
 
7.9%
8 8
 
7.0%
9 5
 
4.4%
7 4
 
3.5%
6 2
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 78
54.9%
, 35
24.6%
: 9
 
6.3%
@ 7
 
4.9%
/ 6
 
4.2%
; 5
 
3.5%
' 2
 
1.4%
Space Separator
ValueCountFrequency (%)
741
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3778
78.6%
Common 1031
 
21.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 388
 
10.3%
o 357
 
9.4%
t 317
 
8.4%
a 306
 
8.1%
i 278
 
7.4%
n 259
 
6.9%
r 236
 
6.2%
s 220
 
5.8%
d 151
 
4.0%
l 141
 
3.7%
Other values (40) 1125
29.8%
Common
ValueCountFrequency (%)
741
71.9%
. 78
 
7.6%
, 35
 
3.4%
0 23
 
2.2%
2 22
 
2.1%
- 18
 
1.7%
5 18
 
1.7%
1 14
 
1.4%
: 9
 
0.9%
4 9
 
0.9%
Other values (11) 64
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4809
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
741
15.4%
e 388
 
8.1%
o 357
 
7.4%
t 317
 
6.6%
a 306
 
6.4%
i 278
 
5.8%
n 259
 
5.4%
r 236
 
4.9%
s 220
 
4.6%
d 151
 
3.1%
Other values (61) 1556
32.4%

school_type2
Text

MISSING 

Distinct9
Distinct (%)10.7%
Missing338
Missing (%)80.1%
Memory size16.5 KiB
2023-12-09T22:21:30.003205image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length32
Median length25
Mean length14.25
Min length10

Characters and Unicode

Total characters1197
Distinct characters28
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)2.4%

Sample

1st rowCTE School
2nd rowAll-Girls School
3rd rowCTE School
4th rowInternational School
5th rowInternational School
ValueCountFrequency (%)
school 85
47.8%
cte 40
22.5%
international 17
 
9.6%
new 16
 
9.0%
specialized 9
 
5.1%
all-girls 8
 
4.5%
all-boys 3
 
1.7%
2023-12-09T22:21:30.281692image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 190
15.9%
l 141
11.8%
94
 
7.9%
S 94
 
7.9%
c 94
 
7.9%
h 85
 
7.1%
e 51
 
4.3%
n 51
 
4.3%
a 43
 
3.6%
i 43
 
3.6%
Other values (18) 311
26.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 814
68.0%
Uppercase Letter 269
 
22.5%
Space Separator 94
 
7.9%
Dash Punctuation 11
 
0.9%
Other Punctuation 9
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 190
23.3%
l 141
17.3%
c 94
11.5%
h 85
10.4%
e 51
 
6.3%
n 51
 
6.3%
a 43
 
5.3%
i 43
 
5.3%
t 34
 
4.2%
r 25
 
3.1%
Other values (6) 57
 
7.0%
Uppercase Letter
ValueCountFrequency (%)
S 94
34.9%
T 40
14.9%
C 40
14.9%
E 40
14.9%
I 17
 
6.3%
N 16
 
5.9%
A 11
 
4.1%
G 8
 
3.0%
B 3
 
1.1%
Space Separator
ValueCountFrequency (%)
94
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1083
90.5%
Common 114
 
9.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 190
17.5%
l 141
13.0%
S 94
 
8.7%
c 94
 
8.7%
h 85
 
7.8%
e 51
 
4.7%
n 51
 
4.7%
a 43
 
4.0%
i 43
 
4.0%
T 40
 
3.7%
Other values (15) 251
23.2%
Common
ValueCountFrequency (%)
94
82.5%
- 11
 
9.6%
, 9
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1197
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 190
15.9%
l 141
11.8%
94
 
7.9%
S 94
 
7.9%
c 94
 
7.9%
h 85
 
7.1%
e 51
 
4.3%
n 51
 
4.3%
a 43
 
3.6%
i 43
 
3.6%
Other values (18) 311
26.0%
Distinct58
Distinct (%)13.7%
Missing0
Missing (%)0.0%
Memory size24.9 KiB
2023-12-09T22:21:30.558696image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1266
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row103
2nd row103
3rd row103
4th row103
5th row103
ValueCountFrequency (%)
203 19
 
4.5%
104 18
 
4.3%
301 14
 
3.3%
209 14
 
3.3%
105 14
 
3.3%
201 13
 
3.1%
302 13
 
3.1%
305 13
 
3.1%
103 12
 
2.8%
206 12
 
2.8%
Other values (48) 280
66.4%
2023-12-09T22:21:30.954638image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 325
25.7%
1 283
22.4%
2 184
14.5%
3 172
13.6%
4 131
10.3%
5 44
 
3.5%
8 35
 
2.8%
9 31
 
2.4%
7 31
 
2.4%
6 30
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1266
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 325
25.7%
1 283
22.4%
2 184
14.5%
3 172
13.6%
4 131
10.3%
5 44
 
3.5%
8 35
 
2.8%
9 31
 
2.4%
7 31
 
2.4%
6 30
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 1266
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 325
25.7%
1 283
22.4%
2 184
14.5%
3 172
13.6%
4 131
10.3%
5 44
 
3.5%
8 35
 
2.8%
9 31
 
2.4%
7 31
 
2.4%
6 30
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1266
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 325
25.7%
1 283
22.4%
2 184
14.5%
3 172
13.6%
4 131
10.3%
5 44
 
3.5%
8 35
 
2.8%
9 31
 
2.4%
7 31
 
2.4%
6 30
 
2.4%
Distinct109
Distinct (%)25.8%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-12-09T22:21:31.254658image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length25
Median length16
Mean length11.90995261
Min length4

Characters and Unicode

Total characters5026
Distinct characters53
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)8.3%

Sample

1st rowLower East Side
2nd rowLower East Side
3rd rowEast Village
4th rowLower East Side
5th rowLower East Side
ValueCountFrequency (%)
east 41
 
5.9%
heights 19
 
2.8%
village 19
 
2.8%
side 18
 
2.6%
harlem 17
 
2.5%
park 17
 
2.5%
district 16
 
2.3%
hills 15
 
2.2%
longwood 15
 
2.2%
williamsburg 14
 
2.0%
Other values (120) 499
72.3%
2023-12-09T22:21:31.684336image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 403
 
8.0%
a 365
 
7.3%
i 356
 
7.1%
l 320
 
6.4%
r 318
 
6.3%
o 306
 
6.1%
s 305
 
6.1%
n 293
 
5.8%
t 279
 
5.6%
268
 
5.3%
Other values (43) 1813
36.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4011
79.8%
Uppercase Letter 714
 
14.2%
Space Separator 268
 
5.3%
Dash Punctuation 18
 
0.4%
Other Punctuation 15
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 403
10.0%
a 365
 
9.1%
i 356
 
8.9%
l 320
 
8.0%
r 318
 
7.9%
o 306
 
7.6%
s 305
 
7.6%
n 293
 
7.3%
t 279
 
7.0%
d 144
 
3.6%
Other values (15) 922
23.0%
Uppercase Letter
ValueCountFrequency (%)
H 82
11.5%
B 82
11.5%
C 74
10.4%
S 69
 
9.7%
L 49
 
6.9%
E 47
 
6.6%
F 41
 
5.7%
W 35
 
4.9%
P 31
 
4.3%
K 27
 
3.8%
Other values (14) 177
24.8%
Other Punctuation
ValueCountFrequency (%)
' 11
73.3%
. 4
 
26.7%
Space Separator
ValueCountFrequency (%)
268
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4725
94.0%
Common 301
 
6.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 403
 
8.5%
a 365
 
7.7%
i 356
 
7.5%
l 320
 
6.8%
r 318
 
6.7%
o 306
 
6.5%
s 305
 
6.5%
n 293
 
6.2%
t 279
 
5.9%
d 144
 
3.0%
Other values (39) 1636
34.6%
Common
ValueCountFrequency (%)
268
89.0%
- 18
 
6.0%
' 11
 
3.7%
. 4
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5026
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 403
 
8.0%
a 365
 
7.3%
i 356
 
7.1%
l 320
 
6.4%
r 318
 
6.3%
o 306
 
6.1%
s 305
 
6.1%
n 293
 
5.8%
t 279
 
5.6%
268
 
5.3%
Other values (43) 1813
36.1%
Distinct117
Distinct (%)27.7%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
2023-12-09T22:21:32.070947image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters2110
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)9.0%

Sample

1st row10002
2nd row10002
3rd row10009
4th row10002
5th row10002
ValueCountFrequency (%)
10457 12
 
2.8%
11101 12
 
2.8%
10002 11
 
2.6%
11201 11
 
2.6%
10456 11
 
2.6%
10468 10
 
2.4%
10019 10
 
2.4%
10473 9
 
2.1%
10451 9
 
2.1%
10011 9
 
2.1%
Other values (107) 318
75.4%
2023-12-09T22:21:32.584574image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 781
37.0%
0 441
20.9%
2 206
 
9.8%
4 184
 
8.7%
3 148
 
7.0%
6 115
 
5.5%
5 98
 
4.6%
7 64
 
3.0%
9 37
 
1.8%
8 36
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2110
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 781
37.0%
0 441
20.9%
2 206
 
9.8%
4 184
 
8.7%
3 148
 
7.0%
6 115
 
5.5%
5 98
 
4.6%
7 64
 
3.0%
9 37
 
1.8%
8 36
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
Common 2110
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 781
37.0%
0 441
20.9%
2 206
 
9.8%
4 184
 
8.7%
3 148
 
7.0%
6 115
 
5.5%
5 98
 
4.6%
7 64
 
3.0%
9 37
 
1.8%
8 36
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2110
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 781
37.0%
0 441
20.9%
2 206
 
9.8%
4 184
 
8.7%
3 148
 
7.0%
6 115
 
5.5%
5 98
 
4.6%
7 64
 
3.0%
9 37
 
1.8%
8 36
 
1.7%
Distinct70
Distinct (%)16.6%
Missing0
Missing (%)0.0%
Memory size24.5 KiB
2023-12-09T22:21:32.889741image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.146919431
Min length1

Characters and Unicode

Total characters906
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.7%

Sample

1st row7
2nd row7
3rd row9
4th row7
5th row7
ValueCountFrequency (%)
42 19
 
4.5%
43 14
 
3.3%
75 13
 
3.1%
40 13
 
3.1%
107 12
 
2.8%
18 12
 
2.8%
48 12
 
2.8%
20 11
 
2.6%
44 11
 
2.6%
13 11
 
2.6%
Other values (60) 294
69.7%
2023-12-09T22:21:33.340363image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 193
21.3%
4 146
16.1%
0 125
13.8%
7 88
9.7%
2 82
9.1%
8 70
 
7.7%
3 67
 
7.4%
5 49
 
5.4%
6 45
 
5.0%
9 41
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 906
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 193
21.3%
4 146
16.1%
0 125
13.8%
7 88
9.7%
2 82
9.1%
8 70
 
7.7%
3 67
 
7.4%
5 49
 
5.4%
6 45
 
5.0%
9 41
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Common 906
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 193
21.3%
4 146
16.1%
0 125
13.8%
7 88
9.7%
2 82
9.1%
8 70
 
7.7%
3 67
 
7.4%
5 49
 
5.4%
6 45
 
5.0%
9 41
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 906
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 193
21.3%
4 146
16.1%
0 125
13.8%
7 88
9.7%
2 82
9.1%
8 70
 
7.7%
3 67
 
7.4%
5 49
 
5.4%
6 45
 
5.0%
9 41
 
4.5%
Distinct32
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Memory size24.3 KiB
2023-12-09T22:21:33.541575image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.623222749
Min length1

Characters and Unicode

Total characters685
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
2 58
 
13.7%
10 28
 
6.6%
9 22
 
5.2%
8 19
 
4.5%
17 18
 
4.3%
11 17
 
4.0%
7 16
 
3.8%
24 15
 
3.6%
14 15
 
3.6%
28 14
 
3.3%
Other values (22) 200
47.4%
2023-12-09T22:21:33.855567image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 190
27.7%
2 173
25.3%
3 56
 
8.2%
7 46
 
6.7%
9 45
 
6.6%
8 44
 
6.4%
0 43
 
6.3%
4 37
 
5.4%
5 30
 
4.4%
6 21
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 685
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 190
27.7%
2 173
25.3%
3 56
 
8.2%
7 46
 
6.7%
9 45
 
6.6%
8 44
 
6.4%
0 43
 
6.3%
4 37
 
5.4%
5 30
 
4.4%
6 21
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
Common 685
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 190
27.7%
2 173
25.3%
3 56
 
8.2%
7 46
 
6.7%
9 45
 
6.6%
8 44
 
6.4%
0 43
 
6.3%
4 37
 
5.4%
5 30
 
4.4%
6 21
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 685
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 190
27.7%
2 173
25.3%
3 56
 
8.2%
7 46
 
6.7%
9 45
 
6.6%
8 44
 
6.4%
0 43
 
6.3%
4 37
 
5.4%
5 30
 
4.4%
6 21
 
3.1%
Distinct255
Distinct (%)60.4%
Missing0
Missing (%)0.0%
Memory size27.5 KiB
2023-12-09T22:21:34.199739image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.514218009
Min length7

Characters and Unicode

Total characters4015
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique178 ?
Unique (%)42.2%

Sample

1st row40.7134809
2nd row40.712235
3rd row40.7298459
4th row40.7205546
5th row40.7194927
ValueCountFrequency (%)
40.8223255 6
 
1.4%
40.839987 6
 
1.4%
40.875163 6
 
1.4%
40.8597019 6
 
1.4%
40.8708801 5
 
1.2%
40.85964 5
 
1.2%
40.717321 5
 
1.2%
40.7748238 5
 
1.2%
40.735387 5
 
1.2%
40.839295 5
 
1.2%
Other values (245) 368
87.2%
2023-12-09T22:21:34.676742image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 664
16.5%
0 581
14.5%
. 422
10.5%
8 391
9.7%
7 363
9.0%
6 334
8.3%
5 269
6.7%
1 254
 
6.3%
9 253
 
6.3%
3 247
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3593
89.5%
Other Punctuation 422
 
10.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 664
18.5%
0 581
16.2%
8 391
10.9%
7 363
10.1%
6 334
9.3%
5 269
7.5%
1 254
 
7.1%
9 253
 
7.0%
3 247
 
6.9%
2 237
 
6.6%
Other Punctuation
ValueCountFrequency (%)
. 422
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4015
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 664
16.5%
0 581
14.5%
. 422
10.5%
8 391
9.7%
7 363
9.0%
6 334
8.3%
5 269
6.7%
1 254
 
6.3%
9 253
 
6.3%
3 247
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4015
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 664
16.5%
0 581
14.5%
. 422
10.5%
8 391
9.7%
7 363
9.0%
6 334
8.3%
5 269
6.7%
1 254
 
6.3%
9 253
 
6.3%
3 247
 
6.2%
Distinct255
Distinct (%)60.4%
Missing0
Missing (%)0.0%
Memory size28.0 KiB
2023-12-09T22:21:35.026211image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.60663507
Min length9

Characters and Unicode

Total characters4476
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique178 ?
Unique (%)42.2%

Sample

1st row-73.9853212
2nd row-73.983823
3rd row-73.9831511
4th row-73.9856836
5th row-73.9791505
ValueCountFrequency (%)
73.8559569 6
 
1.4%
73.837977 6
 
1.4%
73.861653 6
 
1.4%
73.8875889 6
 
1.4%
73.8977529 5
 
1.2%
73.9585007 5
 
1.2%
73.8607428 5
 
1.2%
73.9847013 5
 
1.2%
73.986315 5
 
1.2%
74.0031734 5
 
1.2%
Other values (245) 368
87.2%
2023-12-09T22:21:35.530438image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 686
15.3%
3 660
14.7%
9 527
11.8%
- 422
9.4%
. 422
9.4%
8 402
9.0%
1 260
 
5.8%
5 235
 
5.3%
4 230
 
5.1%
2 217
 
4.8%
Other values (2) 415
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3632
81.1%
Dash Punctuation 422
 
9.4%
Other Punctuation 422
 
9.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 686
18.9%
3 660
18.2%
9 527
14.5%
8 402
11.1%
1 260
 
7.2%
5 235
 
6.5%
4 230
 
6.3%
2 217
 
6.0%
6 216
 
5.9%
0 199
 
5.5%
Dash Punctuation
ValueCountFrequency (%)
- 422
100.0%
Other Punctuation
ValueCountFrequency (%)
. 422
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4476
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 686
15.3%
3 660
14.7%
9 527
11.8%
- 422
9.4%
. 422
9.4%
8 402
9.0%
1 260
 
5.8%
5 235
 
5.3%
4 230
 
5.1%
2 217
 
4.8%
Other values (2) 415
9.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4476
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 686
15.3%
3 660
14.7%
9 527
11.8%
- 422
9.4%
. 422
9.4%
8 402
9.0%
1 260
 
5.8%
5 235
 
5.3%
4 230
 
5.1%
2 217
 
4.8%
Other values (2) 415
9.3%

loc
Text

Distinct255
Distinct (%)60.4%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
2023-12-09T22:21:35.834928image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length38
Median length31
Mean length26.56872038
Min length20

Characters and Unicode

Total characters11212
Distinct characters15
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique178 ?
Unique (%)42.2%

Sample

1st row[-73.98532120000002,40.7134809]
2nd row[-73.983823,40.712235]
3rd row[-73.9831511,40.7298459]
4th row[-73.9856836,40.7205546]
5th row[-73.9791505,40.7194927]
ValueCountFrequency (%)
73.8559569,40.8223255 6
 
1.4%
73.837977,40.839987 6
 
1.4%
73.86165299999999,40.875163 6
 
1.4%
73.8875889,40.8597019 6
 
1.4%
73.8977529,40.8708801 5
 
1.2%
73.911384,40.839295 5
 
1.2%
74.00317339999999,40.743436 5
 
1.2%
73.8607428,40.85964 5
 
1.2%
73.98631499999999,40.593015 5
 
1.2%
73.9931088,40.7653384 5
 
1.2%
Other values (245) 368
87.2%
2023-12-09T22:21:36.291675image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 1985
17.7%
7 1045
9.3%
0 985
8.8%
3 901
8.0%
4 890
7.9%
. 844
 
7.5%
8 811
 
7.2%
6 559
 
5.0%
1 533
 
4.8%
5 493
 
4.4%
Other values (5) 2166
19.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8680
77.4%
Other Punctuation 1266
 
11.3%
Open Punctuation 422
 
3.8%
Dash Punctuation 422
 
3.8%
Close Punctuation 422
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 1985
22.9%
7 1045
12.0%
0 985
11.3%
3 901
10.4%
4 890
10.3%
8 811
9.3%
6 559
 
6.4%
1 533
 
6.1%
5 493
 
5.7%
2 478
 
5.5%
Other Punctuation
ValueCountFrequency (%)
. 844
66.7%
, 422
33.3%
Open Punctuation
ValueCountFrequency (%)
[ 422
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 422
100.0%
Close Punctuation
ValueCountFrequency (%)
] 422
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11212
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 1985
17.7%
7 1045
9.3%
0 985
8.8%
3 901
8.0%
4 890
7.9%
. 844
 
7.5%
8 811
 
7.2%
6 559
 
5.0%
1 533
 
4.8%
5 493
 
4.4%
Other values (5) 2166
19.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11212
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 1985
17.7%
7 1045
9.3%
0 985
8.8%
3 901
8.0%
4 890
7.9%
. 844
 
7.5%
8 811
 
7.2%
6 559
 
5.0%
1 533
 
4.8%
5 493
 
4.4%
Other values (5) 2166
19.3%

context
URL

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size30.6 KiB
http://schema.org
422 
ValueCountFrequency (%)
http://schema.org 422
100.0%
ValueCountFrequency (%)
http 422
100.0%
ValueCountFrequency (%)
schema.org 422
100.0%
ValueCountFrequency (%)
422
100.0%
ValueCountFrequency (%)
422
100.0%
ValueCountFrequency (%)
422
100.0%

type
Text

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size26.1 KiB
2023-12-09T22:21:36.456804image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters2532
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSchool
2nd rowSchool
3rd rowSchool
4th rowSchool
5th rowSchool
ValueCountFrequency (%)
school 422
100.0%
2023-12-09T22:21:36.711454image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 844
33.3%
S 422
16.7%
c 422
16.7%
h 422
16.7%
l 422
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2110
83.3%
Uppercase Letter 422
 
16.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 844
40.0%
c 422
20.0%
h 422
20.0%
l 422
20.0%
Uppercase Letter
ValueCountFrequency (%)
S 422
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2532
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 844
33.3%
S 422
16.7%
c 422
16.7%
h 422
16.7%
l 422
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2532
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 844
33.3%
S 422
16.7%
c 422
16.7%
h 422
16.7%
l 422
16.7%

id
URL

UNIQUE 

Distinct422
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size56.4 KiB
http://nyc.pediacities.com/Resource/School/facing_history_school_the
 
1
http://nyc.pediacities.com/Resource/School/secondary_school_for_journalism
 
1
http://nyc.pediacities.com/Resource/School/frederick_douglass_academy_vii_high_school
 
1
http://nyc.pediacities.com/Resource/School/york_early_college_academy
 
1
http://nyc.pediacities.com/Resource/School/high_school_for_medical_professions
 
1
Other values (417)
417 
ValueCountFrequency (%)
http://nyc.pediacities.com/Resource/School/facing_history_school_the 1
 
0.2%
http://nyc.pediacities.com/Resource/School/secondary_school_for_journalism 1
 
0.2%
http://nyc.pediacities.com/Resource/School/frederick_douglass_academy_vii_high_school 1
 
0.2%
http://nyc.pediacities.com/Resource/School/york_early_college_academy 1
 
0.2%
http://nyc.pediacities.com/Resource/School/high_school_for_medical_professions 1
 
0.2%
http://nyc.pediacities.com/Resource/School/urban_assembly_new_york_harbor_school 1
 
0.2%
http://nyc.pediacities.com/Resource/School/the_metropolitan_soundview_high_school 1
 
0.2%
http://nyc.pediacities.com/Resource/School/bronx_leadership_academy_high_school 1
 
0.2%
http://nyc.pediacities.com/Resource/School/the_global_learning_collaborative 1
 
0.2%
http://nyc.pediacities.com/Resource/School/expeditionary_learning_school_for_community_leaders 1
 
0.2%
Other values (412) 412
97.6%
ValueCountFrequency (%)
http 422
100.0%
ValueCountFrequency (%)
nyc.pediacities.com 422
100.0%
ValueCountFrequency (%)
/Resource/School/heritage_school_the 1
 
0.2%
/Resource/School/community_school_for_social_justice 1
 
0.2%
/Resource/School/middle_college_high_school_at_laguardia_community_college 1
 
0.2%
/Resource/School/juan_morel_campos_secondary_school 1
 
0.2%
/Resource/School/bronx_studio_school_for_writers_and_artists 1
 
0.2%
/Resource/School/secondary_school_for_law 1
 
0.2%
/Resource/School/the_bronxwood_preparatory_academy 1
 
0.2%
/Resource/School/the_college_academy 1
 
0.2%
/Resource/School/kingsborough_early_college_school 1
 
0.2%
/Resource/School/robert_f_kennedy_community_high_school 1
 
0.2%
Other values (412) 412
97.6%
ValueCountFrequency (%)
422
100.0%
ValueCountFrequency (%)
422
100.0%
Distinct258
Distinct (%)61.1%
Missing0
Missing (%)0.0%
Memory size49.5 KiB
2023-12-09T22:21:37.161750image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length85
Median length74
Mean length62.91706161
Min length55

Characters and Unicode

Total characters26551
Distinct characters67
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique182 ?
Unique (%)43.1%

Sample

1st row220 Henry Street New York, NY 10002 (40.7134809, -73.9853212)
2nd row200 Monroe Street New York, NY 10002 (40.712235, -73.983823)
3rd row420 East 12 Street New York, NY 10009 (40.7298459, -73.9831511)
4th row145 Stanton Street New York, NY 10002 (40.7205546, -73.9856836)
5th row111 Columbia Street New York, NY 10002 (40.7194927, -73.9791505)
ValueCountFrequency (%)
ny 422
 
11.2%
avenue 181
 
4.8%
street 157
 
4.2%
brooklyn 118
 
3.1%
bronx 116
 
3.1%
new 103
 
2.7%
york 102
 
2.7%
east 54
 
1.4%
west 47
 
1.2%
road 27
 
0.7%
Other values (1085) 2442
64.8%
2023-12-09T22:21:37.801742image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2536
 
9.6%
1 1615
 
6.1%
0 1561
 
5.9%
4 1221
 
4.6%
3 1213
 
4.6%
7 1205
 
4.5%
e 1085
 
4.1%
8 918
 
3.5%
9 914
 
3.4%
2 859
 
3.2%
Other values (57) 13424
50.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11064
41.7%
Lowercase Letter 6829
25.7%
Space Separator 2536
 
9.6%
Uppercase Letter 2323
 
8.7%
Other Punctuation 1689
 
6.4%
Control 844
 
3.2%
Dash Punctuation 422
 
1.6%
Close Punctuation 422
 
1.6%
Open Punctuation 422
 
1.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 533
22.9%
Y 524
22.6%
B 300
12.9%
A 218
9.4%
S 202
 
8.7%
E 67
 
2.9%
W 54
 
2.3%
R 50
 
2.2%
F 42
 
1.8%
C 41
 
1.8%
Other values (15) 292
12.6%
Lowercase Letter
ValueCountFrequency (%)
e 1085
15.9%
o 732
10.7%
r 716
10.5%
n 699
10.2%
t 615
9.0%
a 438
 
6.4%
l 302
 
4.4%
s 283
 
4.1%
u 259
 
3.8%
k 256
 
3.7%
Other values (14) 1444
21.1%
Decimal Number
ValueCountFrequency (%)
1 1615
14.6%
0 1561
14.1%
4 1221
11.0%
3 1213
11.0%
7 1205
10.9%
8 918
8.3%
9 914
8.3%
2 859
7.8%
5 796
7.2%
6 762
6.9%
Other Punctuation
ValueCountFrequency (%)
, 844
50.0%
. 844
50.0%
' 1
 
0.1%
Space Separator
ValueCountFrequency (%)
2536
100.0%
Control
ValueCountFrequency (%)
844
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 422
100.0%
Close Punctuation
ValueCountFrequency (%)
) 422
100.0%
Open Punctuation
ValueCountFrequency (%)
( 422
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17399
65.5%
Latin 9152
34.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1085
 
11.9%
o 732
 
8.0%
r 716
 
7.8%
n 699
 
7.6%
t 615
 
6.7%
N 533
 
5.8%
Y 524
 
5.7%
a 438
 
4.8%
l 302
 
3.3%
B 300
 
3.3%
Other values (39) 3208
35.1%
Common
ValueCountFrequency (%)
2536
14.6%
1 1615
 
9.3%
0 1561
 
9.0%
4 1221
 
7.0%
3 1213
 
7.0%
7 1205
 
6.9%
8 918
 
5.3%
9 914
 
5.3%
2 859
 
4.9%
, 844
 
4.9%
Other values (8) 4513
25.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26551
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2536
 
9.6%
1 1615
 
6.1%
0 1561
 
5.9%
4 1221
 
4.6%
3 1213
 
4.6%
7 1205
 
4.5%
e 1085
 
4.1%
8 918
 
3.5%
9 914
 
3.4%
2 859
 
3.2%
Other values (57) 13424
50.6%
Distinct5
Distinct (%)1.2%
Missing2
Missing (%)0.5%
Memory size27.3 KiB
2023-12-09T22:21:37.985924image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters3780
Distinct characters18
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMANHATTAN
2nd rowMANHATTAN
3rd rowMANHATTAN
4th rowMANHATTAN
5th rowMANHATTAN
ValueCountFrequency (%)
brooklyn 118
27.4%
bronx 116
27.0%
manhattan 101
23.5%
queens 75
17.4%
staten 10
 
2.3%
is 10
 
2.3%
2023-12-09T22:21:38.266991image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
817
21.6%
N 521
13.8%
O 352
9.3%
A 313
 
8.3%
B 234
 
6.2%
R 234
 
6.2%
T 222
 
5.9%
E 160
 
4.2%
K 118
 
3.1%
L 118
 
3.1%
Other values (8) 691
18.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2963
78.4%
Space Separator 817
 
21.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 521
17.6%
O 352
11.9%
A 313
10.6%
B 234
7.9%
R 234
7.9%
T 222
 
7.5%
E 160
 
5.4%
K 118
 
4.0%
L 118
 
4.0%
Y 118
 
4.0%
Other values (7) 573
19.3%
Space Separator
ValueCountFrequency (%)
817
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2963
78.4%
Common 817
 
21.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 521
17.6%
O 352
11.9%
A 313
10.6%
B 234
7.9%
R 234
7.9%
T 222
 
7.5%
E 160
 
5.4%
K 118
 
4.0%
L 118
 
4.0%
Y 118
 
4.0%
Other values (7) 573
19.3%
Common
ValueCountFrequency (%)
817
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3780
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
817
21.6%
N 521
13.8%
O 352
9.3%
A 313
 
8.3%
B 234
 
6.2%
R 234
 
6.2%
T 222
 
5.9%
E 160
 
4.2%
K 118
 
3.1%
L 118
 
3.1%
Other values (8) 691
18.3%
Distinct51
Distinct (%)12.1%
Missing2
Missing (%)0.5%
Memory size24.3 KiB
2023-12-09T22:21:38.518993image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.757142857
Min length1

Characters and Unicode

Total characters738
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.5%

Sample

1st row1
2nd row1
3rd row2
4th row1
5th row2
ValueCountFrequency (%)
3 22
 
5.2%
33 21
 
5.0%
17 20
 
4.8%
16 19
 
4.5%
1 18
 
4.3%
2 16
 
3.8%
26 15
 
3.6%
8 15
 
3.6%
15 14
 
3.3%
18 13
 
3.1%
Other values (41) 247
58.8%
2023-12-09T22:21:38.895310image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 165
22.4%
3 142
19.2%
2 100
13.6%
4 86
11.7%
6 59
 
8.0%
7 51
 
6.9%
5 44
 
6.0%
8 37
 
5.0%
0 32
 
4.3%
9 22
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 738
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 165
22.4%
3 142
19.2%
2 100
13.6%
4 86
11.7%
6 59
 
8.0%
7 51
 
6.9%
5 44
 
6.0%
8 37
 
5.0%
0 32
 
4.3%
9 22
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
Common 738
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 165
22.4%
3 142
19.2%
2 100
13.6%
4 86
11.7%
6 59
 
8.0%
7 51
 
6.9%
5 44
 
6.0%
8 37
 
5.0%
0 32
 
4.3%
9 22
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 738
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 165
22.4%
3 142
19.2%
2 100
13.6%
4 86
11.7%
6 59
 
8.0%
7 51
 
6.9%
5 44
 
6.0%
8 37
 
5.0%
0 32
 
4.3%
9 22
 
3.0%
Distinct198
Distinct (%)47.1%
Missing2
Missing (%)0.5%
Memory size24.8 KiB
2023-12-09T22:21:39.381640image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.966666667
Min length1

Characters and Unicode

Total characters1246
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)26.0%

Sample

1st row201
2nd row202
3rd row34
4th row3001
5th row2201
ValueCountFrequency (%)
409 10
 
2.4%
135 9
 
2.1%
16 7
 
1.7%
151 7
 
1.7%
194 7
 
1.7%
179 6
 
1.4%
56 6
 
1.4%
213 6
 
1.4%
372 6
 
1.4%
387 6
 
1.4%
Other values (188) 350
83.3%
2023-12-09T22:21:40.473305image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 251
20.1%
3 150
12.0%
2 127
10.2%
5 120
9.6%
0 119
9.6%
9 115
9.2%
4 105
8.4%
7 95
 
7.6%
6 84
 
6.7%
8 80
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1246
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 251
20.1%
3 150
12.0%
2 127
10.2%
5 120
9.6%
0 119
9.6%
9 115
9.2%
4 105
8.4%
7 95
 
7.6%
6 84
 
6.7%
8 80
 
6.4%

Most occurring scripts

ValueCountFrequency (%)
Common 1246
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 251
20.1%
3 150
12.0%
2 127
10.2%
5 120
9.6%
0 119
9.6%
9 115
9.2%
4 105
8.4%
7 95
 
7.6%
6 84
 
6.7%
8 80
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1246
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 251
20.1%
3 150
12.0%
2 127
10.2%
5 120
9.6%
0 119
9.6%
9 115
9.2%
4 105
8.4%
7 95
 
7.6%
6 84
 
6.7%
8 80
 
6.4%

bin
Text

Distinct251
Distinct (%)59.9%
Missing3
Missing (%)0.7%
Memory size26.4 KiB
2023-12-09T22:21:40.906772image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters2933
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique174 ?
Unique (%)41.5%

Sample

1st row1003223
2nd row1003214
3rd row1005974
4th row1004323
5th row1004070
ValueCountFrequency (%)
2074045 6
 
1.4%
2011810 6
 
1.4%
2057045 6
 
1.4%
2022205 6
 
1.4%
3186454 5
 
1.2%
3336215 5
 
1.2%
1083802 5
 
1.2%
2050179 5
 
1.2%
2015241 5
 
1.2%
1017828 5
 
1.2%
Other values (241) 365
87.1%
2023-12-09T22:21:41.455823image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 574
19.6%
1 372
12.7%
3 364
12.4%
2 340
11.6%
4 307
10.5%
5 234
8.0%
8 205
 
7.0%
7 192
 
6.5%
6 192
 
6.5%
9 153
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2933
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 574
19.6%
1 372
12.7%
3 364
12.4%
2 340
11.6%
4 307
10.5%
5 234
8.0%
8 205
 
7.0%
7 192
 
6.5%
6 192
 
6.5%
9 153
 
5.2%

Most occurring scripts

ValueCountFrequency (%)
Common 2933
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 574
19.6%
1 372
12.7%
3 364
12.4%
2 340
11.6%
4 307
10.5%
5 234
8.0%
8 205
 
7.0%
7 192
 
6.5%
6 192
 
6.5%
9 153
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2933
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 574
19.6%
1 372
12.7%
3 364
12.4%
2 340
11.6%
4 307
10.5%
5 234
8.0%
8 205
 
7.0%
7 192
 
6.5%
6 192
 
6.5%
9 153
 
5.2%

bbl
Text

Distinct249
Distinct (%)59.4%
Missing3
Missing (%)0.7%
Memory size27.6 KiB
2023-12-09T22:21:41.744697image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters4190
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique171 ?
Unique (%)40.8%

Sample

1st row1002690041
2nd row1002590044
3rd row1004390017
4th row1003540080
5th row1003350001
ValueCountFrequency (%)
2030590001 6
 
1.4%
2053680001 6
 
1.4%
2046330040 6
 
1.4%
2036040039 6
 
1.4%
1010790029 5
 
1.2%
2028170002 5
 
1.2%
2043580001 5
 
1.2%
1011570025 5
 
1.2%
1008720057 5
 
1.2%
1007420007 5
 
1.2%
Other values (239) 365
87.1%
2023-12-09T22:21:42.152205image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1708
40.8%
1 595
 
14.2%
2 396
 
9.5%
3 366
 
8.7%
4 278
 
6.6%
5 196
 
4.7%
8 181
 
4.3%
6 168
 
4.0%
7 156
 
3.7%
9 146
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4190
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1708
40.8%
1 595
 
14.2%
2 396
 
9.5%
3 366
 
8.7%
4 278
 
6.6%
5 196
 
4.7%
8 181
 
4.3%
6 168
 
4.0%
7 156
 
3.7%
9 146
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
Common 4190
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1708
40.8%
1 595
 
14.2%
2 396
 
9.5%
3 366
 
8.7%
4 278
 
6.6%
5 196
 
4.7%
8 181
 
4.3%
6 168
 
4.0%
7 156
 
3.7%
9 146
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4190
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1708
40.8%
1 595
 
14.2%
2 396
 
9.5%
3 366
 
8.7%
4 278
 
6.6%
5 196
 
4.7%
8 181
 
4.3%
6 168
 
4.0%
7 156
 
3.7%
9 146
 
3.5%

nta
Text

Distinct118
Distinct (%)28.1%
Missing2
Missing (%)0.5%
Memory size54.3 KiB
2023-12-09T22:21:42.508793image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length75
Median length75
Mean length75
Min length75

Characters and Unicode

Total characters31500
Distinct characters55
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)8.3%

Sample

1st rowLower East Side
2nd rowLower East Side
3rd rowEast Village
4th rowChinatown
5th rowLower East Side
ValueCountFrequency (%)
east 40
 
4.1%
park 36
 
3.7%
north 33
 
3.4%
heights 26
 
2.7%
village 26
 
2.7%
hill 24
 
2.5%
south 24
 
2.5%
west 19
 
1.9%
square 18
 
1.8%
hills 15
 
1.5%
Other values (164) 714
73.2%
2023-12-09T22:21:42.991658image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23160
73.5%
e 680
 
2.2%
a 629
 
2.0%
o 612
 
1.9%
r 583
 
1.9%
n 571
 
1.8%
l 541
 
1.7%
t 531
 
1.7%
i 508
 
1.6%
s 423
 
1.3%
Other values (45) 3262
 
10.4%

Most occurring categories

ValueCountFrequency (%)
Space Separator 23160
73.5%
Lowercase Letter 6703
 
21.3%
Uppercase Letter 1321
 
4.2%
Dash Punctuation 302
 
1.0%
Open Punctuation 5
 
< 0.1%
Close Punctuation 5
 
< 0.1%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 680
10.1%
a 629
9.4%
o 612
9.1%
r 583
8.7%
n 571
8.5%
l 541
 
8.1%
t 531
 
7.9%
i 508
 
7.6%
s 423
 
6.3%
h 228
 
3.4%
Other values (15) 1397
20.8%
Uppercase Letter
ValueCountFrequency (%)
H 177
13.4%
C 150
11.4%
B 149
11.3%
S 116
 
8.8%
M 89
 
6.7%
P 88
 
6.7%
E 61
 
4.6%
N 58
 
4.4%
W 55
 
4.2%
V 54
 
4.1%
Other values (14) 324
24.5%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
' 1
 
25.0%
Space Separator
ValueCountFrequency (%)
23160
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 302
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23476
74.5%
Latin 8024
 
25.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 680
 
8.5%
a 629
 
7.8%
o 612
 
7.6%
r 583
 
7.3%
n 571
 
7.1%
l 541
 
6.7%
t 531
 
6.6%
i 508
 
6.3%
s 423
 
5.3%
h 228
 
2.8%
Other values (39) 2718
33.9%
Common
ValueCountFrequency (%)
23160
98.7%
- 302
 
1.3%
( 5
 
< 0.1%
) 5
 
< 0.1%
. 3
 
< 0.1%
' 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23160
73.5%
e 680
 
2.2%
a 629
 
2.0%
o 612
 
1.9%
r 583
 
1.9%
n 571
 
1.8%
l 541
 
1.7%
t 531
 
1.7%
i 508
 
1.6%
s 423
 
1.3%
Other values (45) 3262
 
10.4%